Triple

T22663867
Position Surface form Disambiguated ID Type / Status
Subject Professor Marston and the Wonder Women E559730 entity
Predicate musicBy P1952 FINISHED
Object Tom Howe NE NERFINISHED

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: Tom Howe | Statement: [Professor Marston and the Wonder Women, musicBy, Tom Howe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Howe
Context triple: [Professor Marston and the Wonder Women, musicBy, Tom Howe]
  • A. Tom Howe chosen
    Tom Howe is a British composer best known for his work on film and television scores, including the acclaimed series "Ted Lasso."
  • B. Bob Houghton
    Bob Houghton is an English football manager best known for his influential tactical innovations in the 1970s, including leading Malmö FF to the 1979 European Cup final.
  • C. John Clemons
    John Clemons is an individual whose specific public notability or profession is not clearly identifiable from the given information.
  • D. Thomas Oaster
    Thomas Oaster is an American men's rights advocate best known for initiating and promoting the observance that became International Men's Day.
  • E. Joe Crawford
    Joe Crawford is a former Major League Baseball umpire known for his long career and work in numerous postseason games.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2454a158c819093b8e35f5045efb6 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f176617ed8819095a58a2c9f1e3918 completed April 29, 2026, 3:09 a.m.
Created at: April 17, 2026, 3:08 p.m.