Triple

T2080993
Position Surface form Disambiguated ID Type / Status
Subject Sally Ride Science E45240 entity
Predicate foundedBy P104 FINISHED
Object Jill Messick E287731 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: Jill Messick | Statement: [Sally Ride Science, foundedBy, Jill Messick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jill Messick
Context triple: [Sally Ride Science, foundedBy, Jill Messick]
  • A. Jill Messick chosen
    Jill Messick was an American film producer and entertainment executive who co-founded Sally Ride Science and worked on several notable Hollywood projects.
  • B. Jill Bilcock
    Jill Bilcock is an acclaimed Australian film editor known for her work on major films such as "Moulin Rouge!", "Romeo + Juliet," and "Elizabeth."
  • C. Carolyn Hockett
    Carolyn Hockett is known for being one of the later wives of American actor and entertainer Mickey Rooney.
  • D. Roberta Seidman
    Roberta Seidman was the wife of American actor John Garfield, a prominent film star of the 1930s and 1940s.
  • E. Janet M. Lang
    Janet M. Lang is a scholar and co-author known for her collaborative work with James G. Blight on Cold War history and crisis decision-making.
  • 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_69a8891869c88190a02643e3bb746f59 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba345be48190a1895f388e7749e5 completed March 7, 2026, 5:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69b12de0989481909ce71f3fb739ac2a completed March 11, 2026, 8:54 a.m.
Created at: March 4, 2026, 7:41 p.m.