Triple

T9624365
Position Surface form Disambiguated ID Type / Status
Subject Woman series E232421 entity
Predicate hasPart P35 FINISHED
Object Woman V E810247 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: Woman V | Statement: [Woman series, hasPart, Woman V]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Woman V
Context triple: [Woman series, hasPart, Woman V]
  • A. Woman V chosen
    Woman V is an artwork that forms part of Willem de Kooning’s renowned abstract expressionist “Woman” series.
  • B. Woman
    Woman is a documentary film by Yann Arthus-Bertrand that presents intimate interviews with women around the world, exploring their experiences, challenges, and perspectives.
  • C. Woman
    "Woman" is a 1996 feminist-themed song by Swedish singer-songwriter Neneh Cherry, known for its empowering lyrics and response to James Brown’s "It's a Man's Man's Man's World."
  • D. Woman I
    Woman I is a landmark abstract expressionist painting by Willem de Kooning, renowned for its aggressive brushwork and provocative depiction of the female figure.
  • E. Women
    "Women" is a semi-autobiographical novel by Charles Bukowski that follows his hard-drinking alter ego Henry Chinaski through a series of raw, often chaotic relationships with various women.
  • 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_69ca848793ec8190a93a12383a754dc0 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9ad76b148190a38fadee06594db4 completed April 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69d182291c34819099f3f43769849c5d completed April 4, 2026, 9:27 p.m.
Created at: March 30, 2026, 8:10 p.m.