Triple

T36704286
Position Surface form Disambiguated ID Type / Status
Subject Efficient Estimation of Word Representations in Vector Space E906311 entity
Predicate evaluationTask P96882 FINISHED
Object word similarity LITERAL FINISHED

How this triple was built (2 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: word similarity | Statement: [Efficient Estimation of Word Representations in Vector Space, evaluationTask, word similarity]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: evaluationTask
Context triple: [Efficient Estimation of Word Representations in Vector Space, evaluationTask, word similarity]
  • A. evaluationModel
    Indicates a relationship where one entity serves as a model, standard, or framework used to assess, judge, or measure the performance or quality of another entity.
  • B. evaluationAspect chosen
    Indicates the specific dimension or criterion of performance or quality that is being assessed within an evaluation.
  • C. evaluationRole
    Indicates the role or capacity in which an entity participates in an evaluation or assessment process.
  • D. evaluationUse
    Indicates that something is used as a basis, tool, or resource for evaluating or assessing something else.
  • E. evaluationBasis
    Indicates the criteria, standards, or reference framework used to judge, assess, or measure something in an evaluation process.
  • F. None of above.

Provenance (3 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_69f76e7195c48190b5580c9cfb01e95f completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c9f5a8848190ba956ff27f44e396 completed May 3, 2026, 10:19 p.m.
PD Predicate disambiguation batch_69f7c8999a348190abc1895eaa6e036d completed May 3, 2026, 10:13 p.m.
Created at: May 3, 2026, 4:12 p.m.