Triple

T10710366
Position Surface form Disambiguated ID Type / Status
Subject Roger Whittaker E252517 entity
Predicate familyName P18 FINISHED
Object Whittaker E147626 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: Whittaker | Statement: [Roger Whittaker, familyName, Whittaker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Whittaker
Context triple: [Roger Whittaker, familyName, Whittaker]
  • A. Whittaker chosen
    Whittaker is a surname of English and Scottish origin borne by various notable individuals across fields such as science, sports, and the arts.
  • B. Whitaker
    Whitaker is an English surname commonly borne by individuals in the United Kingdom and the United States, associated with various notable figures across politics, sports, and the arts.
  • C. Red Whittaker
    Red Whittaker is a pioneering American roboticist known for his groundbreaking work in field robotics, autonomous vehicles, and planetary exploration systems.
  • D. Woolsey
    Woolsey is a surname most notably associated with Theodore Dwight Woolsey, a prominent 19th-century American academic and president of Yale College.
  • E. Fisher
    Fisher is a common English surname borne by numerous notable individuals across fields such as economics, politics, entertainment, and sports.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fe515b1081909532a20b61ff6cf0 completed April 9, 2026, 1:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9990f220081909dae41bcec8b4768 completed April 11, 2026, 12:42 a.m.
Created at: April 8, 2026, 9:13 p.m.