Triple

T5142665
Position Surface form Disambiguated ID Type / Status
Subject Sharon Stone E115995 entity
Predicate notableWork P4 FINISHED
Object Catwoman E135917 NE 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: Catwoman | Statement: [Sharon Stone, notableWork, Catwoman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catwoman
Context triple: [Sharon Stone, notableWork, Catwoman]
  • A. Selina Kyle chosen
    Selina Kyle is a cunning and morally ambiguous cat burglar in the Batman universe, best known by her alter ego Catwoman.
  • B. Kate Kane
    Kate Kane is the DC Comics superheroine who becomes Batwoman, a vigilante crime-fighter in Gotham City and cousin to Bruce Wayne.
  • C. Harley Quinn
    Harley Quinn is a chaotic, acrobatic antiheroine from DC Comics known for her clown-themed appearance, unpredictable behavior, and complex relationship with the Joker.
  • D. Margaret Lemon
    Margaret Lemon is a fictional character on the television series "30 Rock," known as the overbearing and critical mother of protagonist Liz Lemon.
  • E. Batwoman
    Batwoman is a DC Comics superheroine and crimefighter, often depicted as a wealthy vigilante in Gotham City who operates independently of Batman.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69bd4446c0e08190a7c29dc74976bf03 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd787ff1c081909a6954aa76e12cbf completed March 20, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69becfec5c108190a3882c25118179a7 completed March 21, 2026, 5:05 p.m.
Created at: March 20, 2026, 1:43 p.m.