Triple

T16624641
Position Surface form Disambiguated ID Type / Status
Subject Jak E403914 entity
Predicate ally P4662 FINISHED
Object Keira Hagai E1224648 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: Keira Hagai | Statement: [Jak, ally, Keira Hagai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keira Hagai
Context triple: [Jak, ally, Keira Hagai]
  • A. Keira Hagai chosen
    Keira Hagai is a skilled mechanic and hovercraft engineer who serves as Jak’s close ally and love interest in the Jak and Daxter video game series.
  • B. Kirsha Kaechele
    Kirsha Kaechele is an American-born artist, curator, and social entrepreneur known for her experimental community projects and work with the Museum of Old and New Art (MONA) in Tasmania.
  • C. Rebecca Dayan
    Rebecca Dayan is a French actress and model known for her roles in film and television, including portraying Elsa Peretti in the Netflix miniseries "Halston."
  • D. Keira Malik
    Keira Malik is the daughter of British-Pakistani actor Art Malik.
  • E. Tali Sasson
    Tali Sasson is an Israeli lawyer and former state prosecutor best known for authoring the 2005 Sasson Report on illegal outposts in the West Bank.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37550ee308190931fd50aeebe1e7e completed April 18, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084b7b94481909dfc0dd7b009a5b4 completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:17 a.m.