Triple

T22788184
Position Surface form Disambiguated ID Type / Status
Subject Anna Draper E564030 entity
Predicate familyName P18 FINISHED
Object Draper 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: Draper | Statement: [Anna Draper, familyName, Draper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Draper
Context triple: [Anna Draper, familyName, Draper]
  • A. Draper chosen
    Draper is a surname of English origin borne by various notable individuals across fields such as science, politics, and the arts.
  • B. Draper
    Draper is a suburban city in the southeastern part of the Salt Lake Valley in Utah, known for its residential communities, tech industry presence, and outdoor recreation opportunities.
  • C. Peabody
    Peabody is a suburban city in northeastern Massachusetts known for its location on the North Shore and its historical ties to the leather industry.
  • D. Peabody
    Peabody is the middle name of the American ethnologist and linguist J. P. Harrington, known for his extensive documentation of Native American languages and cultures.
  • E. Norwood
    Norwood is a locality in South Africa situated near the town of Houghton, known primarily as a residential suburb.
  • 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_69e2455500788190b4b33030461f3bbd completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17c33be7c8190ad22391a85fa000d completed April 29, 2026, 3:34 a.m.
Created at: April 17, 2026, 3:29 p.m.