Triple

T20069200
Position Surface form Disambiguated ID Type / Status
Subject dependency grammar E499688 entity
Predicate hasVariant P455 FINISHED
Object Functional Generative Description NE NERFINISHED

How this triple was built (3 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: Functional Generative Description | Statement: [dependency grammar, hasVariant, Functional Generative Description]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Functional Generative Description
Context triple: [dependency grammar, hasVariant, Functional Generative Description]
  • 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. General and Rational Grammar
    General and Rational Grammar is a 17th-century French linguistic treatise from the Port-Royal school that seeks to explain the universal, rational principles underlying all human languages.
  • C. 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.
  • D. Generative Phonology: Description and Theory
    Generative Phonology: Description and Theory is a foundational textbook in theoretical linguistics that systematically presents the principles and methods of generative phonology.
  • E. Standard Theory of generative grammar
    The Standard Theory of generative grammar is an early framework in Noam Chomsky’s generative linguistics that formalizes how deep structures are transformed into surface structures to explain the syntax of natural languages.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Functional Generative Description
Target entity description: Functional Generative Description is a theoretical framework within dependency grammar that models sentence structure through functionally motivated, generative rules linking form and meaning.
  • 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. General and Rational Grammar
    General and Rational Grammar is a 17th-century French linguistic treatise from the Port-Royal school that seeks to explain the universal, rational principles underlying all human languages.
  • C. 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.
  • D. Generative Phonology: Description and Theory
    Generative Phonology: Description and Theory is a foundational textbook in theoretical linguistics that systematically presents the principles and methods of generative phonology.
  • E. Standard Theory of generative grammar
    The Standard Theory of generative grammar is an early framework in Noam Chomsky’s generative linguistics that formalizes how deep structures are transformed into surface structures to explain the syntax of natural languages.
  • F. None of above. chosen

Provenance (2 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e664365ad0819089103b00d1cf8c9f completed April 20, 2026, 5:36 p.m.
Created at: April 11, 2026, 3:39 p.m.