Triple

T19997480
Position Surface form Disambiguated ID Type / Status
Subject Jonquel Jones E494232 entity
Predicate givenName P17 FINISHED
Object Jonquel 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: Jonquel | Statement: [Jonquel Jones, givenName, Jonquel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonquel
Context triple: [Jonquel Jones, givenName, Jonquel]
  • A. Jonquel chosen
    Jonquel is the given name of Jonquel Jones, a professional basketball player known for her standout career in the WNBA and international competitions.
  • B. Eyraud
    Eyraud is a French surname most notably borne by Eugène Eyraud, a 19th-century missionary known for his work on Easter Island.
  • C. Jougne
    Jougne is a small French commune in the Doubs department of the Bourgogne-Franche-Comté region, known for its location near the Swiss border in the Jura Mountains.
  • D. Baulmes
    Baulmes is a Swiss village and municipality in the canton of Vaud, situated near the Jura Mountains and known for its scenic rural landscape.
  • E. Locquénolé
    Locquénolé is a small coastal commune in the Finistère department of Brittany in northwestern France, known for its picturesque setting on the Bay of Morlaix.
  • 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_69e65fe549108190947a4d1a587c08f8 completed April 20, 2026, 5:18 p.m.
Created at: April 11, 2026, 3:32 p.m.