Triple

T5633147
Position Surface form Disambiguated ID Type / Status
Subject Ashe Marson E147880 entity
Predicate associatedWith P37 FINISHED
Object Joan Valentine E152728 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: Joan Valentine | Statement: [Ashe Marson, associatedWith, Joan Valentine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joan Valentine
Context triple: [Ashe Marson, associatedWith, Joan Valentine]
  • A. Joan Valentine chosen
    Joan Valentine is a quick-witted, resourceful young woman who works as a journalist and adventurer in P. G. Wodehouse’s comic fiction.
  • B. Aileen Marlowe
    Aileen Marlowe was the wife of American film and television actor Hugh Marlowe.
  • C. Letty Aronson
    Letty Aronson is an American film producer best known for her long-running collaboration with director Woody Allen on numerous critically acclaimed movies.
  • D. Claire de Loone
    Claire de Loone is a prim, intellectual anthropologist and one of the three main female leads in the classic Broadway musical "On the Town."
  • E. Vina Wray
    Vina Wray is an alternate name for Fay Wray, the Canadian-American actress best known for her iconic role in the 1933 film "King Kong."
  • 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_69c00907bc8881909ed760d3ed73ef35 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0225ff3248190b93c9f5887553fd4 completed March 22, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d69128881909870e8901f967e80 completed March 22, 2026, 8:13 p.m.
Created at: March 22, 2026, 3:41 p.m.