Triple

T20069202
Position Surface form Disambiguated ID Type / Status
Subject dependency grammar E499688 entity
Predicate hasVariant P455 FINISHED
Object Universal Dependencies framework (as an annotation scheme)
The Universal Dependencies framework is a cross-linguistically consistent annotation scheme for grammatical relations in natural language corpora, designed to support multilingual parsing and comparative linguistic research.
E1410550 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: Universal Dependencies framework (as an annotation scheme) | Statement: [dependency grammar, hasVariant, Universal Dependencies framework (as an annotation scheme)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Universal Dependencies framework (as an annotation scheme)
Context triple: [dependency grammar, hasVariant, Universal Dependencies framework (as an annotation scheme)]
  • A. Types of A-bar Dependencies
    Types of A-bar Dependencies is a seminal linguistics monograph by Guglielmo Cinque that analyzes the structure and behavior of A-bar movement and related syntactic dependencies across languages.
  • B. UDC syntactic relations
    UDC syntactic relations are the standardized rules and symbols used in the Universal Decimal Classification system to express complex subject relationships and combinations between classification numbers.
  • C. Augmented Transition Network
    Augmented Transition Network is a type of finite-state machine extended with stack-based memory and procedural actions, widely used in natural language processing for parsing complex sentence structures.
  • D. Stanford CoreNLP
    Stanford CoreNLP is a widely used, open-source natural language processing toolkit that provides a broad range of linguistic analysis tools such as tokenization, parsing, and named entity recognition.
  • E. Tree Adjoining Grammar
    Tree Adjoining Grammar is a highly structured formal grammar framework in computational linguistics used to model the syntax of natural languages with greater expressive power than context-free grammars.
  • 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: Universal Dependencies framework (as an annotation scheme)
Triple: [dependency grammar, hasVariant, Universal Dependencies framework (as an annotation scheme)]
Generated description
The Universal Dependencies framework is a cross-linguistically consistent annotation scheme for grammatical relations in natural language corpora, designed to support multilingual parsing and comparative linguistic research.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Universal Dependencies framework (as an annotation scheme)
Target entity description: The Universal Dependencies framework is a cross-linguistically consistent annotation scheme for grammatical relations in natural language corpora, designed to support multilingual parsing and comparative linguistic research.
  • A. Types of A-bar Dependencies
    Types of A-bar Dependencies is a seminal linguistics monograph by Guglielmo Cinque that analyzes the structure and behavior of A-bar movement and related syntactic dependencies across languages.
  • B. UDC syntactic relations
    UDC syntactic relations are the standardized rules and symbols used in the Universal Decimal Classification system to express complex subject relationships and combinations between classification numbers.
  • C. Augmented Transition Network
    Augmented Transition Network is a type of finite-state machine extended with stack-based memory and procedural actions, widely used in natural language processing for parsing complex sentence structures.
  • D. Stanford CoreNLP
    Stanford CoreNLP is a widely used, open-source natural language processing toolkit that provides a broad range of linguistic analysis tools such as tokenization, parsing, and named entity recognition.
  • E. Tree Adjoining Grammar
    Tree Adjoining Grammar is a highly structured formal grammar framework in computational linguistics used to model the syntax of natural languages with greater expressive power than context-free grammars.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e664365ad0819089103b00d1cf8c9f completed April 20, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a081f3acb7881908e23b1d066c35051 completed May 16, 2026, 7:39 a.m.
NEDg Description generation batch_6a081fbb7f208190a032f9f312fd07de completed May 16, 2026, 7:41 a.m.
NED2 Entity disambiguation (via description) batch_6a08208c203c819083abea34d10d5e4e completed May 16, 2026, 7:45 a.m.
Created at: April 11, 2026, 3:39 p.m.