{"id":13841,"date":"2025-10-06T15:12:17","date_gmt":"2025-10-06T15:12:17","guid":{"rendered":"https:\/\/www.nizamuddeen.com\/community\/?p=13841"},"modified":"2026-06-18T18:37:51","modified_gmt":"2026-06-18T18:37:51","slug":"what-is-truth-conditional-semantics","status":"publish","type":"post","link":"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/","title":{"rendered":"What is Truth-Conditional Semantics?"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"13841\" class=\"elementor elementor-13841\" data-elementor-post-type=\"post\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6f06bb62 e-flex e-con-boxed e-con e-parent\" data-id=\"6f06bb62\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7b7c2997 elementor-widget elementor-widget-text-editor\" data-id=\"7b7c2997\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<blockquote><p>A sentence&#8217;s meaning is specified by the <strong>conditions under which it would be true<\/strong>; formally, a theory of meaning <strong>pairs sentences with truth conditions<\/strong> inside a model (entities, functions, relations). This model-theoretic view traces to Tarski&#8217;s work on defining truth for formal languages and is foundational in modern formal semantics (e.g., Heim &amp; Kratzer).<\/p><\/blockquote><p>When we interpret a sentence, we implicitly ask: <em>under what conditions would this sentence be true?<\/em> This simple but profound question forms the basis of <strong>truth-conditional semantics<\/strong>. Instead of treating language as mere word associations, this framework treats meaning as a set of <strong>truth conditions<\/strong> that link language to reality.<\/p><p>In search, truth-conditional semantics shifts the goal from matching strings to <strong>verifying facts<\/strong>. It ensures that retrieved results not only exhibit <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-semantic-relevance\/\" rel=\"noopener\">semantic relevance<\/a> but also align with the <strong>logical correctness<\/strong> of the user&#8217;s query.<\/p><h2><span class=\"ez-toc-section\" id=\"Tarski_and_the_Birth_of_Truth_in_Language\"><\/span>Tarski and the Birth of Truth in Language<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-ans\"><p>The foundations of truth-conditional semantics come from <strong>Alfred Tarski&#8217;s definition of truth<\/strong> in formal languages. Tarski proposed that:<\/p><\/div> <p><em>&#8220;Snow is white&#8221; is true if and only if snow is white.<\/em><\/p><p>This correspondence view ties sentences to the <strong>world they describe<\/strong>, providing a model-theoretic anchor. For search, this means every query &#8211; document match should be checked not only for <strong>lexical overlap<\/strong> but for <strong>truthful grounding in the knowledge base or evidence sources<\/strong>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6ec8fd5 e-flex e-con-boxed e-con e-parent\" data-id=\"6ec8fd5\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2da1719 elementor-widget elementor-widget-text-editor\" data-id=\"2da1719\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>[dflip id=&#8221;17016&#8243;][\/dflip<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-b7b6336 e-flex e-con-boxed e-con e-parent\" data-id=\"b7b6336\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-588277a elementor-align-center elementor-mobile-align-center elementor-widget elementor-widget-button\" data-id=\"588277a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/www.nizamuddeen.com\/community\/wp-content\/uploads\/2026\/01\/What-is-Truth-Conditional-Semantics_-1.pdf\" target=\"_blank\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download PDF!<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-ec22b55 e-flex e-con-boxed e-con e-parent\" data-id=\"ec22b55\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cef48e1 elementor-widget elementor-widget-text-editor\" data-id=\"cef48e1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2><span class=\"ez-toc-section\" id=\"Montague_Semantics_Natural_Language_Meets_Logic\"><\/span>Montague Semantics: Natural Language Meets Logic<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-ans\"><p>Richard Montague extended these ideas by treating natural language with the rigor of <strong>formal logic<\/strong>. His framework introduced:<\/p><\/div><div class=\"ls-cards\"><div class=\"ls-card\"><p class=\"ls-card-h\">Possible Worlds Semantics<\/p><p>A sentence&#8217;s truth depends on which worlds it holds in (e.g., &#8220;Unicorns exist&#8221; is false in the actual world but could be true in an imagined one).<\/p><\/div><div class=\"ls-card\"><p class=\"ls-card-h\">Compositional Semantics<\/p><p>The meaning of a whole expression is built systematically from its parts, much like in <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-sequence-modeling-in-nlp\/\" rel=\"noopener\">sequence modeling<\/a>.<\/p><\/div><\/div><p>For semantic search, Montague&#8217;s insights underpin the idea that meaning is <strong>composable and context-sensitive<\/strong>, queries can be rewritten or expanded using <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-query-augmentation\/\" rel=\"noopener\">query augmentation<\/a> to align truth conditions more closely with documents.<\/p><hr class=\"ls-divider\"><h2><span class=\"ez-toc-section\" id=\"Heim_Kratzer_Context_and_Dynamic_Meaning\"><\/span>Heim &amp; Kratzer: Context and Dynamic Meaning<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-ans\"><p>Building on Montague, Irene Heim and Angelika Kratzer advanced truth-conditional semantics into the <strong>dynamic era<\/strong>. They showed that meaning is not static but interacts with <strong>context and discourse<\/strong>.<\/p><\/div><p><strong>Example<\/strong>: <em>&#8220;Ali bought a phone. It is expensive.&#8221;<\/em><\/p><p style=\"padding-left: 40px;\">The truth of &#8220;It is expensive&#8221; depends on correctly linking &#8220;it&#8221; to &#8220;phone.&#8221;<\/p><p>This introduces <strong>contextual hierarchy<\/strong> into semantics, where truth conditions are updated across sentences and sessions. For search, it explains why multi-turn queries require <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-are-context-vectors\/\" rel=\"noopener\">context vectors<\/a> to preserve truth across evolving user intent.<\/p><hr class=\"ls-divider\"><h2><span class=\"ez-toc-section\" id=\"Possible_Worlds_and_Search_Interpretation\"><\/span>Possible Worlds and Search Interpretation<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-ans\"><p>Truth-conditional semantics also accounts for <strong>modality and hypotheticals<\/strong>, which appear frequently in queries.<\/p><\/div><ul><li><p>Query: <em>&#8220;Could Bitcoin reach $100k?&#8221;<\/em><\/p><\/li><li><p>Truth condition: Evaluated not in the actual world but across possible financial scenarios.<\/p><\/li><\/ul><p>Here, <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-a-knowledge-domain\/\" rel=\"noopener\">knowledge domains<\/a> determine which &#8220;worlds&#8221; matter, finance vs. linguistics vs. gaming. Search engines must resolve ambiguity by mapping queries to the right domain and evaluating truth within that model.<\/p><hr class=\"ls-divider\"><h2><span class=\"ez-toc-section\" id=\"Why_Truth-Conditional_Semantics_Matters_for_Search\"><\/span>Why Truth-Conditional Semantics Matters for Search<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-ans\"><p>Truth-conditional semantics forces search engines to ask a deeper question than &#8220;Does this document match the query?&#8221; Instead, the focus becomes:<\/p><\/div><p style=\"padding-left: 40px;\"><strong>Does the document support the truth of the query&#8217;s proposition?<\/strong><\/p><p>This aligns naturally with <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-knowledge-based-trust\/\" rel=\"noopener\">knowledge-based trust<\/a> and moves search closer to <strong>fact-checking by design<\/strong>. By anchoring meaning in truth conditions, engines ensure that queries resolve not only into semantically similar results but into <strong>factually correct answers<\/strong>.<\/p><hr class=\"ls-divider\"><h2><span class=\"ez-toc-section\" id=\"From_Meaning_to_Verifiable_Claims\"><\/span>From Meaning to Verifiable Claims<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-ans\"><p>Truth-conditional semantics offers a rigorous target for search: a query or statement is meaningful only if we can determine <strong>the conditions under which it is true<\/strong>. For search engines, this means going beyond <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-semantic-similarity\/\" rel=\"noopener\">semantic similarity<\/a> and focusing on <strong>factual alignment with evidence<\/strong>.<\/p><\/div><p>Operationalizing this requires transforming natural language into <strong>structured claims<\/strong> that can be checked. For example:<\/p><ul><li><p>Query: <em>&#8220;Did Tesla acquire SolarCity?&#8221;<\/em><\/p><\/li><li><p>Representation: Acquire(Tesla, SolarCity).<\/p><\/li><\/ul><p>By aligning claims with entities in an <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-an-entity-graph\/\" rel=\"noopener\">entity graph<\/a>, search systems can verify whether evidence supports or refutes the statement. This claim-based design ensures that results move beyond relevance toward <strong>truthful retrieval<\/strong>.<\/p><hr class=\"ls-divider\"><h2><span class=\"ez-toc-section\" id=\"Engineering_a_Truth-Verification_Pipeline\"><\/span>Engineering a Truth-Verification Pipeline<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-ans\"><p>A practical truth-conditional pipeline integrates <strong>retrieval, inference, and verification<\/strong>:<\/p><\/div><div class=\"ls-cards\"><div class=\"ls-card\"><div class=\"ls-card-head\"><span class=\"ls-num\">1<\/span><p class=\"ls-card-h\">Claim Extraction<\/p><\/div><p><br \/>Parse queries into logical or claim-like structures, using <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-query-optimization\/\" rel=\"noopener\">query optimization<\/a> to normalize them into canonical forms.<\/p><\/div><div class=\"ls-card\"><div class=\"ls-card-head\"><span class=\"ls-num\">2<\/span><p class=\"ls-card-h\">Evidence Retrieval<\/p><\/div><p><br \/>Collect passages via dense retrieval and filter with <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-passage-ranking\/\" rel=\"noopener\">passage ranking<\/a> to prioritize sources most likely to support or refute the claim.<\/p><\/div><div class=\"ls-card\"><div class=\"ls-card-head\"><span class=\"ls-num\">3<\/span><p class=\"ls-card-h\">Entailment Inference<\/p><\/div><p><br \/>Apply textual inference models to decide whether evidence entails, contradicts, or leaves the claim unresolved.<\/p><\/div><div class=\"ls-card\"><div class=\"ls-card-head\"><span class=\"ls-num\">4<\/span><p class=\"ls-card-h\">Verification and Attribution<\/p><\/div><p><br \/>Link claims back to evidence spans, grounding them in trusted documents and ensuring <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-knowledge-based-trust\/\" rel=\"noopener\">knowledge-based trust<\/a>.<\/p><\/div><\/div><p>This structure mirrors how fact-checking systems and <strong>RAG (retrieval-augmented generation)<\/strong> pipelines enforce factual correctness in responses.<\/p><hr class=\"ls-divider\"><h2><span class=\"ez-toc-section\" id=\"Evaluation_Metrics_for_Truth-Conditional_Search\"><\/span>Evaluation Metrics for Truth-Conditional Search<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-ans\"><p>Traditional relevance metrics like precision and recall do not guarantee correctness. Truth-conditional evaluation requires new measures:<\/p><\/div><div class=\"ls-cards\"><div class=\"ls-card\"><p class=\"ls-card-h\">Entailment Accuracy<\/p><p>whether the system correctly identifies if evidence supports or contradicts a claim.<\/p><\/div><div class=\"ls-card\"><p class=\"ls-card-h\">Evidence Attribution<\/p><p>proportion of system outputs that can be directly traced to a cited source, aligning with <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-query-serp-mapping\/\" rel=\"noopener\">query &#8211; SERP mapping<\/a>.<\/p><\/div><div class=\"ls-card\"><p class=\"ls-card-h\">Factual Faithfulness<\/p><p>percentage of generated outputs that do not introduce hallucinated content, similar to measuring <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-update-score\/\" rel=\"noopener\">update score<\/a> in freshness-sensitive contexts.<\/p><\/div><div class=\"ls-card\"><p class=\"ls-card-h\">Task Completion<\/p><p>session-level evaluation of whether users received a factually correct, actionable answer.<\/p><\/div><\/div><p>These metrics place truth at the center of evaluation, ensuring search engines are judged not just on relevance, but on <strong>factual reliability<\/strong>.<\/p><hr class=\"ls-divider\"><h2><span class=\"ez-toc-section\" id=\"UX_Patterns_for_Truth-Aware_Search\"><\/span>UX Patterns for Truth-Aware Search<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-ans\"><p>Truth-conditional reasoning also reshapes how results should be presented:<\/p><\/div><div class=\"ls-cards\"><div class=\"ls-card\"><p class=\"ls-card-h\">Evidence-first snippets<\/p><p>show the supporting passage alongside the claim, improving transparency.<\/p><\/div><div class=\"ls-card\"><p class=\"ls-card-h\">Contradiction flags<\/p><p>if evidence diverges, highlight the disagreement to avoid misleading users.<\/p><\/div><div class=\"ls-card\"><p class=\"ls-card-h\">Attribution highlights<\/p><p>emphasize <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-attribute-prominence\/\" rel=\"noopener\">attribute prominence<\/a> by making sources, dates, and claims visible at a glance.<\/p><\/div><div class=\"ls-card\"><p class=\"ls-card-h\">Session clarifiers<\/p><p>when queries evolve over time, carry forward truth-conditional constraints so that <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-user-context-based-search-engine\/\" rel=\"noopener\">user-context-based search<\/a> preserves factual consistency across sessions.<\/p><\/div><\/div><p>By integrating truth-awareness into the interface, search engines not only return relevant documents but also signal <strong>factual correctness<\/strong> clearly to the user.<\/p><hr class=\"ls-divider\"><h2><span class=\"ez-toc-section\" id=\"Future_Directions_Truth_at_Scale\"><\/span>Future Directions: Truth at Scale<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-ans\"><p>The next evolution in truth-conditional search will be driven by three trends:<\/p><\/div><div class=\"ls-cards\"><div class=\"ls-card\"><div class=\"ls-card-head\"><span class=\"ls-num\">1<\/span><p class=\"ls-card-h\">LLM Verification Loops<\/p><\/div><p>large models applying self-checking strategies (plan &#8211; verify &#8211; revise) to reduce hallucination in generated answers.<\/p><\/div><div class=\"ls-card\"><div class=\"ls-card-head\"><span class=\"ls-num\">2<\/span><p class=\"ls-card-h\">Cross-lingual Fact Verification<\/p><\/div><p>aligning truth-conditional semantics across languages using multilingual embeddings and <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-a-knowledge-domain\/\" rel=\"noopener\">knowledge domains<\/a>.<\/p><\/div><div class=\"ls-card\"><div class=\"ls-card-head\"><span class=\"ls-num\">3<\/span><p class=\"ls-card-h\">Temporal Truth Modeling<\/p><\/div><p>embedding time-sensitive claims into <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-are-context-vectors\/\" rel=\"noopener\">context vectors<\/a> so that truth is evaluated not just in general, but in the <strong>right timeframe<\/strong>.<\/p><\/div><\/div><p>Together, these advances signal a future where search engines evolve from being <strong>relevance-driven<\/strong> to being <strong>truth-driven<\/strong>.<\/p><hr class=\"ls-divider\"><h2><span class=\"ez-toc-section\" id=\"Last_Thoughts_on_Truth-conditional_semantics\"><\/span>Last Thoughts on Truth-conditional semantics<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"ls-takeaways\"><h3><span class=\"ez-toc-section\" id=\"Key_Takeaways\"><\/span>Key Takeaways<span class=\"ez-toc-section-end\"><\/span><\/h3><ul><li>Truth-conditional semantics defines a sentence&#8217;s meaning by the conditions under which it would be true, evaluated inside a model of entities and relations.<\/li><li>Tarski&#8217;s correspondence principle grounds meaning in the world, pushing search to verify facts rather than only match strings.<\/li><li>Montague added compositional and possible-worlds semantics, explaining how meaning is built from parts and varies by scenario.<\/li><li>A truth-verification pipeline chains claim extraction, evidence retrieval, entailment inference, and attribution to confirm or refute a query.<\/li><li>Queries can be represented as structured claims and checked against an entity graph to move retrieval from relevance toward correctness.<\/li><li>Truth-aware evaluation adds metrics such as entailment accuracy, evidence attribution, and factual faithfulness beyond precision and recall.<\/li><\/ul><\/div><div class=\"ls-ans\"><p>Truth-conditional semantics reframes search from simply &#8220;matching text&#8221; to <strong>verifying reality<\/strong>. By grounding queries in logical conditions and linking them with trustworthy evidence, search engines can guarantee not only semantic alignment but factual correctness.<\/p><\/div><p>Just as <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-semantic-similarity\/\" rel=\"noopener\">semantic similarity<\/a> advanced relevance, truth-conditional pipelines push search toward <strong>evidence-based trust<\/strong>, making queries map not only to meaning, but to the <strong>truth conditions under which that meaning holds<\/strong>.<\/p><hr class=\"ls-divider\"><h2><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions_FAQs\"><\/span>Frequently Asked Questions (FAQs)<span class=\"ez-toc-section-end\"><\/span><\/h2><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"How_is_truth-conditional_semantics_different_from_semantic_similarity\"><\/span><strong>How is truth-conditional semantics different from semantic similarity?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>Semantic similarity measures closeness in meaning, while truth-conditional semantics asks whether a claim is <strong>factually correct given evidence<\/strong>.<\/p><\/details><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"Why_does_search_need_truth-conditional_semantics\"><\/span><strong>Why does search need truth-conditional semantics?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>Because users expect not just relevant results but <strong>verified correctness<\/strong>. By aligning with <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-knowledge-based-trust\/\" rel=\"noopener\">knowledge-based trust<\/a>, truth-conditional systems ensure reliable answers.<\/p><\/details><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"Can_truth_conditions_handle_evolving_information\"><\/span><strong>Can truth conditions handle evolving information?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>Yes, by embedding temporal signals via <a class=\"decorated-link\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-update-score\/\" rel=\"noopener\">update score<\/a> and session-based context, systems adapt truth judgments to the current state of the world.<\/p><\/details><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"What_is_truth-conditional_semantics\"><\/span>What is truth-conditional semantics?<span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>Truth-conditional semantics is the view that a sentence&#8217;s meaning is specified by the conditions under which it would be true. Formally, a theory of meaning pairs sentences with truth conditions inside a model made of entities, functions, and relations. In search, it shifts the goal from matching strings to verifying whether retrieved results align with the logical correctness of a query.<\/p><\/details><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"What_did_Tarski_contribute_to_truth-conditional_semantics\"><\/span>What did Tarski contribute to truth-conditional semantics?<span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>Alfred Tarski defined truth for formal languages using the correspondence principle that a sentence like Snow is white is true if and only if snow is white. This ties sentences to the world they describe and provides a model-theoretic anchor for meaning. For search, it implies that a query and document match should be checked for truthful grounding in evidence, not just lexical overlap.<\/p><\/details><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"How_does_Montague_semantics_relate_to_search\"><\/span>How does Montague semantics relate to search?<span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>Richard Montague treated natural language with the rigor of formal logic, introducing possible worlds semantics and compositional meaning. Compositionality means the meaning of an expression is built systematically from its parts, much like sequence modeling. This supports the idea that queries can be rewritten or expanded so their truth conditions align more closely with documents.<\/p><\/details><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"What_is_the_role_of_possible_worlds_in_evaluating_queries\"><\/span>What is the role of possible worlds in evaluating queries?<span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>Possible worlds semantics says a sentence&#8217;s truth depends on which worlds it holds in, which matters for modal or hypothetical queries. A question such as Could Bitcoin reach a given price is evaluated across possible scenarios rather than only the actual world. Search systems must map the query to the right domain and evaluate truth within that model.<\/p><\/details><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"What_does_a_truth-verification_pipeline_look_like\"><\/span>What does a truth-verification pipeline look like?<span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>A practical pipeline combines claim extraction, evidence retrieval, entailment inference, and verification with attribution. Queries are parsed into claim-like structures, relevant passages are retrieved and ranked, and inference models decide whether evidence supports, contradicts, or leaves the claim unresolved. Claims are then linked back to evidence spans to ground them in trusted sources.<\/p><\/details><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"How_are_natural_language_queries_turned_into_verifiable_claims\"><\/span>How are natural language queries turned into verifiable claims?<span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>Truth-conditional design transforms natural language into structured claims that can be checked against evidence. For example, the query Did one company acquire another becomes a relation such as Acquire applied to the two entities. Aligning these claims with entities in an entity graph lets the system verify whether evidence supports or refutes the statement.<\/p><\/details><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"What_metrics_measure_truth-conditional_search_quality\"><\/span>What metrics measure truth-conditional search quality?<span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>Traditional precision and recall do not guarantee correctness, so additional measures are used. These include entailment accuracy, which checks if evidence is correctly judged to support or contradict a claim, evidence attribution, which tracks whether outputs trace to a cited source, and factual faithfulness, which measures the absence of hallucinated content. Task completion adds a session-level view of whether the user got a correct, actionable answer.<\/p><\/details><details class=\"ls-faq\"><summary><h3><span class=\"ez-toc-section\" id=\"What_UX_patterns_help_present_truth-aware_results\"><\/span>What UX patterns help present truth-aware results?<span class=\"ez-toc-section-end\"><\/span><\/h3><\/summary><p>Truth-aware interfaces use evidence-first snippets that show the supporting passage alongside the claim. Contradiction flags highlight disagreement when sources diverge, and attribution highlights make sources, dates, and claims visible at a glance. Session clarifiers carry truth-conditional constraints forward so factual consistency is preserved as queries evolve.<\/p><\/details>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-aa0307b elementor-section-content-middle elementor-reverse-tablet elementor-reverse-mobile elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"aa0307b\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-c2592c7\" data-id=\"c2592c7\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8bc9dfc elementor-widget elementor-widget-heading\" data-id=\"8bc9dfc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<p class=\"elementor-heading-title elementor-size-default\">Want to Go Deeper into SEO?<\/p>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a6b0add elementor-widget elementor-widget-text-editor\" data-id=\"a6b0add\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"302\" data-end=\"342\">Explore more from my SEO knowledge base:<\/p><p data-start=\"344\" data-end=\"744\">\u25aa\ufe0f <strong data-start=\"478\" data-end=\"564\"><a class=\"\" href=\"https:\/\/www.nizamuddeen.com\/seo-hub-content-marketing\/\" target=\"_blank\" rel=\"noopener\" data-start=\"480\" data-end=\"562\">SEO &amp; Content Marketing Hub<\/a><\/strong> \u2014 Learn how content builds authority and visibility<br data-start=\"616\" data-end=\"619\" \/>\u25aa\ufe0f <strong data-start=\"611\" data-end=\"714\"><a class=\"\" href=\"https:\/\/www.nizamuddeen.com\/community\/search-engine-semantics\/\" target=\"_blank\" rel=\"noopener\" data-start=\"613\" data-end=\"712\">Search Engine Semantics Hub<\/a><\/strong> \u2014 A resource on entities, meaning, and search intent<br \/>\u25aa\ufe0f <strong data-start=\"622\" data-end=\"685\"><a class=\"\" href=\"https:\/\/www.nizamuddeen.com\/academy\/\" target=\"_blank\" rel=\"noopener\" data-start=\"624\" data-end=\"683\">Join My SEO Academy<\/a><\/strong> \u2014 Step-by-step guidance for beginners to advanced learners<\/p><p data-start=\"746\" data-end=\"857\">Whether you&#8217;re learning, growing, or scaling, you&#8217;ll find everything you need to <strong data-start=\"831\" data-end=\"856\">build real SEO 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class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download Now!<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 ez-toc-wrap-right counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 eztoc-toggle-hide-by-default' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Tarski_and_the_Birth_of_Truth_in_Language\" >Tarski and the Birth of Truth in Language<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Montague_Semantics_Natural_Language_Meets_Logic\" >Montague Semantics: Natural Language Meets Logic<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Heim_Kratzer_Context_and_Dynamic_Meaning\" >Heim &amp; Kratzer: Context and Dynamic Meaning<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Possible_Worlds_and_Search_Interpretation\" >Possible Worlds and Search Interpretation<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Why_Truth-Conditional_Semantics_Matters_for_Search\" >Why Truth-Conditional Semantics Matters for Search<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#From_Meaning_to_Verifiable_Claims\" >From Meaning to Verifiable Claims<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Engineering_a_Truth-Verification_Pipeline\" >Engineering a Truth-Verification Pipeline<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Evaluation_Metrics_for_Truth-Conditional_Search\" >Evaluation Metrics for Truth-Conditional Search<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#UX_Patterns_for_Truth-Aware_Search\" >UX Patterns for Truth-Aware Search<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Future_Directions_Truth_at_Scale\" >Future Directions: Truth at Scale<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Last_Thoughts_on_Truth-conditional_semantics\" >Last Thoughts on Truth-conditional semantics<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Key_Takeaways\" >Key Takeaways<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Frequently_Asked_Questions_FAQs\" >Frequently Asked Questions (FAQs)<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#How_is_truth-conditional_semantics_different_from_semantic_similarity\" >How is truth-conditional semantics different from semantic similarity?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Why_does_search_need_truth-conditional_semantics\" >Why does search need truth-conditional semantics?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#Can_truth_conditions_handle_evolving_information\" >Can truth conditions handle evolving information?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#What_is_truth-conditional_semantics\" >What is truth-conditional semantics?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#What_did_Tarski_contribute_to_truth-conditional_semantics\" >What did Tarski contribute to truth-conditional semantics?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#How_does_Montague_semantics_relate_to_search\" >How does Montague semantics relate to search?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#What_is_the_role_of_possible_worlds_in_evaluating_queries\" >What is the role of possible worlds in evaluating queries?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#What_does_a_truth-verification_pipeline_look_like\" >What does a truth-verification pipeline look like?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-22\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#How_are_natural_language_queries_turned_into_verifiable_claims\" >How are natural language queries turned into verifiable claims?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-23\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#What_metrics_measure_truth-conditional_search_quality\" >What metrics measure truth-conditional search quality?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-24\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/#What_UX_patterns_help_present_truth-aware_results\" >What UX patterns help present truth-aware results?<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n","protected":false},"excerpt":{"rendered":"<p>A sentence&#8217;s meaning is specified by the conditions under which it would be true; formally, a theory of meaning pairs sentences with truth conditions inside a model (entities, functions, relations). This model-theoretic view traces to Tarski&#8217;s work on defining truth for formal languages and is foundational in modern formal semantics (e.g., Heim &amp; Kratzer). When [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":21581,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_ls_faq_schema":"{\"@context\": \"https:\/\/schema.org\", \"@type\": \"FAQPage\", \"mainEntity\": [{\"@type\": \"Question\", \"name\": \"How is truth-conditional semantics different from semantic similarity?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Semantic similarity measures closeness in meaning, while truth-conditional semantics asks whether a claim is factually correct given evidence.\"}}, {\"@type\": \"Question\", \"name\": \"Why does search need truth-conditional semantics?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Because users expect not just relevant results but verified correctness. By aligning with knowledge-based trust, truth-conditional systems ensure reliable answers.\"}}, {\"@type\": \"Question\", \"name\": \"Can truth conditions handle evolving information?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Yes, by embedding temporal signals via update score and session-based context, systems adapt truth judgments to the current state of the world.\"}}, {\"@type\": \"Question\", \"name\": \"What is truth-conditional semantics?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Truth-conditional semantics is the view that a sentence's meaning is specified by the conditions under which it would be true. Formally, a theory of meaning pairs sentences with truth conditions inside a model made of entities, functions, and relations. In search, it shifts the goal from matching strings to verifying whether retrieved results align with the logical correctness of a query.\"}}, {\"@type\": \"Question\", \"name\": \"What did Tarski contribute to truth-conditional semantics?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Alfred Tarski defined truth for formal languages using the correspondence principle that a sentence like Snow is white is true if and only if snow is white. This ties sentences to the world they describe and provides a model-theoretic anchor for meaning. For search, it implies that a query and document match should be checked for truthful grounding in evidence, not just lexical overlap.\"}}, {\"@type\": \"Question\", \"name\": \"How does Montague semantics relate to search?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Richard Montague treated natural language with the rigor of formal logic, introducing possible worlds semantics and compositional meaning. Compositionality means the meaning of an expression is built systematically from its parts, much like sequence modeling. This supports the idea that queries can be rewritten or expanded so their truth conditions align more closely with documents.\"}}, {\"@type\": \"Question\", \"name\": \"What is the role of possible worlds in evaluating queries?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Possible worlds semantics says a sentence's truth depends on which worlds it holds in, which matters for modal or hypothetical queries. A question such as Could Bitcoin reach a given price is evaluated across possible scenarios rather than only the actual world. Search systems must map the query to the right domain and evaluate truth within that model.\"}}, {\"@type\": \"Question\", \"name\": \"What does a truth-verification pipeline look like?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"A practical pipeline combines claim extraction, evidence retrieval, entailment inference, and verification with attribution. Queries are parsed into claim-like structures, relevant passages are retrieved and ranked, and inference models decide whether evidence supports, contradicts, or leaves the claim unresolved. Claims are then linked back to evidence spans to ground them in trusted sources.\"}}, {\"@type\": \"Question\", \"name\": \"How are natural language queries turned into verifiable claims?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Truth-conditional design transforms natural language into structured claims that can be checked against evidence. For example, the query Did one company acquire another becomes a relation such as Acquire applied to the two entities. Aligning these claims with entities in an entity graph lets the system verify whether evidence supports or refutes the statement.\"}}, {\"@type\": \"Question\", \"name\": \"What metrics measure truth-conditional search quality?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Traditional precision and recall do not guarantee correctness, so additional measures are used. These include entailment accuracy, which checks if evidence is correctly judged to support or contradict a claim, evidence attribution, which tracks whether outputs trace to a cited source, and factual faithfulness, which measures the absence of hallucinated content. Task completion adds a session-level view of whether the user got a correct, actionable answer.\"}}, {\"@type\": \"Question\", \"name\": \"What UX patterns help present truth-aware results?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Truth-aware interfaces use evidence-first snippets that show the supporting passage alongside the claim. Contradiction flags highlight disagreement when sources diverge, and attribution highlights make sources, dates, and claims visible at a glance. Session clarifiers carry truth-conditional constraints forward so factual consistency is preserved as queries evolve.\"}}]}","footnotes":""},"categories":[161],"tags":[],"class_list":["post-13841","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-semantics"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>What is Truth-Conditional Semantics?<\/title>\n<meta name=\"description\" content=\"A sentence&#039;s meaning is specified by the conditions under which it would be true; formally, a theory of meaning pairs sentences with truth conditions inside.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.nizamuddeen.com\/community\/semantics\/what-is-truth-conditional-semantics\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What is Truth-Conditional Semantics?\" \/>\n<meta property=\"og:description\" content=\"A sentence&#039;s meaning is specified by the conditions under which it would be true; 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