Triple

T20473442
Position Surface form Disambiguated ID Type / Status
Subject GoldenEye 007 E502252 entity
Predicate developer P73 FINISHED
Object Rare NE NERFINISHED

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: Rare | Statement: [GoldenEye 007, developer, Rare]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rare
Context triple: [GoldenEye 007, developer, Rare]
  • A. Rare chosen
    Rare is a renowned British video game developer known for creating influential titles such as Donkey Kong Country, GoldenEye 007, Banjo-Kazooie, and Sea of Thieves.
  • B. Rare
    Rare is Selena Gomez's third studio album, a pop record known for its themes of self-acceptance and emotional resilience.
  • C. Rarity
    Rarity is a main character from the My Little Pony franchise, known as a stylish unicorn fashion designer with a generous and dramatic personality.
  • D. Rare Junk
    Rare Junk is an album produced by William E. McEuen, known for its eclectic blend of folk, country, and experimental sounds.
  • E. Rare Finds
    Rare Finds is a hospitality brand under Kerzner International that focuses on distinctive, character-rich hotels and resorts offering unique, locally inspired experiences.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4ae5f1081908768b0c9a3a0bf38 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69962d810819091bb13fe73250e24 completed April 20, 2026, 9:23 p.m.
Created at: April 16, 2026, 11:33 a.m.