Triple

T4724669
Position Surface form Disambiguated ID Type / Status
Subject Mr. Tappitt E104851 entity
Predicate workFirstPublishedIn P15299 FINISHED
Object Rachel Ray E18094 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: Rachel Ray | Statement: [Mr. Tappitt, workFirstPublishedIn, Rachel Ray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel Ray
Context triple: [Mr. Tappitt, workFirstPublishedIn, Rachel Ray]
  • A. Rachel Ray chosen
    "Rachel Ray" is a 19th-century novel by Anthony Trollope that explores themes of love, religious influence, and social pressure in a small English town.
  • B. Rachel Ray
    Rachael Ray is an American television personality, celebrity chef, and author best known for her quick and easy cooking style and shows like "30 Minute Meals."
  • C. Sandra Lee
    Sandra Lee is an American television chef and author known for her "Semi-Homemade" cooking concept and numerous Food Network shows.
  • D. Anna LoPizzo
    Anna LoPizzo was an Italian immigrant mill worker whose death during the 1912 Lawrence textile strike became a pivotal rallying point for the labor movement in the United States.
  • E. Paula Stewart
    Paula Stewart is an American actress and singer known for her work on Broadway and in television during the mid-20th century.
  • 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_69bd43ed84648190ae0b7ee8e8d00482 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64456a6c8190b658216b62ef82cf completed March 20, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be39ff21f0819094a273a0f26b22f4 completed March 21, 2026, 6:26 a.m.
Created at: March 20, 2026, 1:18 p.m.