Triple

T7346727
Position Surface form Disambiguated ID Type / Status
Subject GrabCar E169397 entity
Predicate competesWith P1375 FINISHED
Object Maxim E338749 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: Maxim | Statement: [GrabCar, competesWith, Maxim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maxim
Context triple: [GrabCar, competesWith, Maxim]
  • A. Maxim chosen
    Maxim is a masculine given name of Latin origin, commonly used in Slavic and other European countries.
  • B. Mark Francois
    Mark Francois is a British Conservative politician and Member of Parliament known for his roles in defence-related ministerial posts and his prominent support for Brexit.
  • C. Alexandr Wang
    Alexandr Wang is an American entrepreneur best known as the co-founder and CEO of AI data company Scale AI.
  • D. Bronson
    Bronson is a 2008 British biographical crime film in which Tom Hardy portrays the notoriously violent prisoner Charles Bronson.
  • E. Bronson
    Bronson is a given name most notably associated with American educator and transcendentalist philosopher Amos Bronson Alcott.
  • 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_69c68a5878888190968ce4d04db8d69f completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0f0329c8190a0182e3bf62604e5 completed March 27, 2026, 9:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa916ac881909acee8184b71dc85 completed March 28, 2026, 3:58 p.m.
Created at: March 27, 2026, 3:05 p.m.