Triple

T20002940
Position Surface form Disambiguated ID Type / Status
Subject William Clifford Musselman E494380 entity
Predicate familyName P18 FINISHED
Object Musselman 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: Musselman | Statement: [William Clifford Musselman, familyName, Musselman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Musselman
Context triple: [William Clifford Musselman, familyName, Musselman]
  • A. Musselman chosen
    Musselman is a surname most notably associated with American basketball coaches Bill Musselman and his son Eric Musselman.
  • B. Mullins
    Mullins is an English-language surname of Irish and Norman origin borne by various notable individuals across history.
  • C. Munson
    Munson is an art museum in Utica, New York, known for its diverse collection of American and European works and its role as a regional cultural center.
  • D. Mullett
    Mullett is a surname most notably associated with Alfred B. Mullett, a 19th-century American architect known for designing prominent federal buildings.
  • E. Mathieson
    Mathieson is a surname of Scottish origin, typically regarded as a variant of Matheson and derived from a patronymic meaning “son of Matthew.”
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a2e34481908a495cc5d077c41f completed April 20, 2026, 5:25 p.m.
Created at: April 11, 2026, 3:33 p.m.