Triple

T13653509
Position Surface form Disambiguated ID Type / Status
Subject Theta Theory E326797 entity
Predicate relatedTo P37 FINISHED
Object Lexical-Functional Grammar
Lexical-Functional Grammar is a non-transformational theory of syntax that models sentence structure through parallel levels of representation, emphasizing the relationship between grammatical functions and lexical information.
E1053408 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lexical-Functional Grammar | Statement: [Theta Theory, relatedTo, Lexical-Functional Grammar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lexical-Functional Grammar
Context triple: [Theta Theory, relatedTo, Lexical-Functional Grammar]
  • A. Word Formation in Generative Grammar
    Word Formation in Generative Grammar is a foundational linguistics monograph that systematically analyzes how words are structured and created within the framework of generative grammar.
  • B. Mathematical Structures of Language
    Mathematical Structures of Language is a foundational work in mathematical linguistics that applies formal and algebraic methods to analyze the structure of natural languages.
  • C. Lectures on Government and Binding
    Lectures on Government and Binding is a foundational book by Noam Chomsky that systematically presents the Government and Binding framework in generative syntax.
  • D. An Introduction to Syntactic Theory
    An Introduction to Syntactic Theory is a foundational linguistics textbook that presents the core concepts and analytical tools of generative syntax.
  • E. Adverbs and Functional Heads: A Cross-Linguistic Perspective
    Adverbs and Functional Heads: A Cross-Linguistic Perspective is a seminal syntactic study by Guglielmo Cinque that argues for a richly articulated hierarchy of functional projections to explain the distribution of adverbs and related elements across languages.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lexical-Functional Grammar
Triple: [Theta Theory, relatedTo, Lexical-Functional Grammar]
Generated description
Lexical-Functional Grammar is a non-transformational theory of syntax that models sentence structure through parallel levels of representation, emphasizing the relationship between grammatical functions and lexical information.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lexical-Functional Grammar
Target entity description: Lexical-Functional Grammar is a non-transformational theory of syntax that models sentence structure through parallel levels of representation, emphasizing the relationship between grammatical functions and lexical information.
  • A. Word Formation in Generative Grammar
    Word Formation in Generative Grammar is a foundational linguistics monograph that systematically analyzes how words are structured and created within the framework of generative grammar.
  • B. Mathematical Structures of Language
    Mathematical Structures of Language is a foundational work in mathematical linguistics that applies formal and algebraic methods to analyze the structure of natural languages.
  • C. Lectures on Government and Binding
    Lectures on Government and Binding is a foundational book by Noam Chomsky that systematically presents the Government and Binding framework in generative syntax.
  • D. An Introduction to Syntactic Theory
    An Introduction to Syntactic Theory is a foundational linguistics textbook that presents the core concepts and analytical tools of generative syntax.
  • E. Adverbs and Functional Heads: A Cross-Linguistic Perspective
    Adverbs and Functional Heads: A Cross-Linguistic Perspective is a seminal syntactic study by Guglielmo Cinque that argues for a richly articulated hierarchy of functional projections to explain the distribution of adverbs and related elements across languages.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc60ace048190a4b92310ba272bd1 completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78affa3c481909dba71e2ce9f44c1 completed May 3, 2026, 5:50 p.m.
NEDg Description generation batch_69f78d1d7de88190a61c554aa27c439d completed May 3, 2026, 5:59 p.m.
NED2 Entity disambiguation (via description) batch_69f78e00007c81909007a751fd4625c2 completed May 3, 2026, 6:03 p.m.
Created at: April 9, 2026, 9:52 p.m.