Triple

T12491764
Position Surface form Disambiguated ID Type / Status
Subject Reminisce E298581 entity
Predicate hasCollaboratedWith P8554 FINISHED
Object Vector E988193 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: Vector | Statement: [Reminisce, hasCollaboratedWith, Vector]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vector
Context triple: [Reminisce, hasCollaboratedWith, Vector]
  • A. Vector
    Vector is a mid-range, sport-oriented trim level of the Saab 9-3 that typically offers enhanced performance and upgraded interior and exterior features compared to base models.
  • B. Vector
    Vector is a villainous character from the Despicable Me franchise, known for his orange tracksuit, bowl haircut, and high-tech gadgets.
  • C. Vector
    Vector is a commercial vehicle brand produced by the Russian automotive manufacturer GAZ Group, known primarily for its buses.
  • D. Vector chosen
    Vector is a prominent Nigerian rapper and songwriter known for his intricate wordplay, punchlines, and influential presence in the country’s hip-hop scene.
  • E. Vectors
    "Vectors" is a science fiction work by American author Michael Kube-McDowell, known for its exploration of complex futuristic and technological themes.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94de3076c81909640c982d520ca6b completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65eaabadc81908f8af6bc10ce3238 completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 9:56 p.m.