Triple

T2250582
Position Surface form Disambiguated ID Type / Status
Subject Emilia Clarke E49606 entity
Predicate name P16 FINISHED
Object Emilia Clarke E49606 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: Emilia Clarke | Statement: [Emilia Clarke, name, Emilia Clarke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emilia Clarke
Context triple: [Emilia Clarke, name, Emilia Clarke]
  • A. Emilia Clarke chosen
    Emilia Clarke is an English actress best known for her role as Daenerys Targaryen in the television series "Game of Thrones."
  • B. Lena Headey
    Lena Headey is an English actress best known for playing Cersei Lannister in the television series "Game of Thrones."
  • C. Sophie Turner
    Sophie Turner is an English actress best known for her role as Sansa Stark in the television series "Game of Thrones."
  • D. Gwendoline Christie
    Gwendoline Christie is an English actress best known for her role as Brienne of Tarth in the television series "Game of Thrones" and as Captain Phasma in the "Star Wars" sequel trilogy.
  • E. Felicity Jones
    Felicity Jones is an English actress known for her roles in films such as "The Theory of Everything" and "Rogue One: A Star Wars Story."
  • 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_69a88aaa9250819095e127d0d77e8a32 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc11b61888190af3b11b87dc8e0dc completed March 7, 2026, 6:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71c487908190903e06bcb2393484 completed March 9, 2026, 7:07 a.m.
Created at: March 4, 2026, 7:47 p.m.