Triple

T18902235
Position Surface form Disambiguated ID Type / Status
Subject Battle Circle series E462363 entity
Predicate mainCharacter P1183 FINISHED
Object Var 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: Var | Statement: [Battle Circle series, mainCharacter, Var]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Var
Context triple: [Battle Circle series, mainCharacter, Var]
  • A. Var
    Var is a department in southeastern France known for its Mediterranean coastline, including popular resort areas along the French Riviera.
  • B. Var chosen
    Var is a Norse goddess associated with oaths, agreements, and the punishment of those who break them.
  • C. Vars
    Vars is a French alpine commune and ski resort village located in the Hautes-Alpes department in southeastern France.
  • D. VAR
    VAR (Video Assistant Referee) is a football officiating system that uses video technology to help referees review and correct clear and obvious errors in key match situations.
  • E. VAR
    VAR is the three-letter IATA airport code assigned to Varna Airport in Varna, Bulgaria.
  • 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_69d8dcfd05bc819088903cca13cc2846 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c52a4b4c8190b5821996e3c1741d completed April 20, 2026, 6:18 a.m.
Created at: April 10, 2026, 11:58 a.m.