Triple

T8863900
Position Surface form Disambiguated ID Type / Status
Subject Mary Dows Herter Norton E210962 entity
Predicate familyName P18 FINISHED
Object Norton E89028 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: Norton | Statement: [Mary Dows Herter Norton, familyName, Norton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norton
Context triple: [Mary Dows Herter Norton, familyName, Norton]
  • A. Norton chosen
    Norton is a surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
  • B. Norton
    Norton is a small town in Bristol County, southeastern Massachusetts, known for being home to Wheaton College and several scenic ponds and conservation areas.
  • C. Norton
    Norton is a historic British motorcycle manufacturer renowned for its success in mid-20th-century road racing and the Isle of Man TT.
  • D. Norton
    Norton is a residential suburb within the town of Runcorn in Cheshire, England.
  • E. Norton
    Norton is a town in Zimbabwe located near the Manyame River, known for its agricultural activities and proximity to the capital, Harare.
  • 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_69ca838bbddc8190ab546d737e5d350f completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc610416b48190a26f0c457089ffca completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0caccd88190b6464f53d0239e47 completed April 3, 2026, 11:13 a.m.
Created at: March 30, 2026, 6:50 p.m.