Triple

T36083841
Position Surface form Disambiguated ID Type / Status
Subject Article III:2 E1043722 entity
Predicate firstSentenceStandard P137462 FINISHED
Object like products 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: like products | Statement: [Article III:2, firstSentenceStandard, like products]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: firstSentenceStandard
Context triple: [Article III:2, firstSentenceStandard, like products]
  • A. initialSentence chosen
    Indicates that the referenced sentence is the first or opening sentence in a text, document, or discourse.
  • B. firstStandard
    Indicates that the subject is the earliest or primary instance in a defined standard, sequence, or set of reference criteria.
  • C. secondSentenceStandard
    Indicates that the referenced text is the second sentence according to a standard or canonical sentence segmentation.
  • D. firstWord
    Indicates that one entity is the first word in the sequence or text associated with another entity.
  • E. firstOrdinary
    Indicates that the subject is the first entity to hold or occupy an ordinary (non-special, standard) position, role, or status in a given sequence or context.
  • 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_69f76e3154908190a6f702671c2bea08 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_6a037c8d06cc8190ab6a5e18d9d2571e completed May 12, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a037a0895b48190acdd88dc10db7be7 completed May 12, 2026, 7:05 p.m.
Created at: May 3, 2026, 4:08 p.m.