Triple

T10458013
Position Surface form Disambiguated ID Type / Status
Subject Empire Award for Best Actress E246595 entity
Predicate notableRecipient P108 FINISHED
Object Emma Watson E117460 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: Emma Watson | Statement: [Empire Award for Best Actress, notableRecipient, Emma Watson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emma Watson
Context triple: [Empire Award for Best Actress, notableRecipient, Emma Watson]
  • A. Emma Watson chosen
    Emma Watson is a British actress and activist best known for playing Hermione Granger in the Harry Potter film series and for her advocacy on gender equality.
  • B. Evanna Lynch
    Evanna Lynch is an Irish actress best known for playing Luna Lovegood in the Harry Potter film series.
  • C. Hannah Murray
    Hannah Murray is an English actress best known for her roles as Cassie Ainsworth in the TV series "Skins" and Gilly in "Game of Thrones."
  • D. Diana Patricia Hiddleston
    Diana Patricia Hiddleston is the mother of English actor Tom Hiddleston.
  • E. Lily James
    Lily James is an English actress known for her roles in films such as Cinderella, Baby Driver, and Mamma Mia! Here We Go Again, as well as the TV series Downton Abbey.
  • 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fe4a56e08190ab56d762d6a91b01 completed April 7, 2026, 12:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69d87f182cb481909f838d6d1dfa7e79 completed April 10, 2026, 4:39 a.m.
Created at: April 6, 2026, 12:18 p.m.