Triple

T2490300
Position Surface form Disambiguated ID Type / Status
Subject Carlos Arroyo E52023 entity
Predicate playedFor P2170 FINISHED
Object Beşiktaş Milangaz E31354 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: Beşiktaş Milangaz | Statement: [Carlos Arroyo, playedFor, Beşiktaş Milangaz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beşiktaş Milangaz
Context triple: [Carlos Arroyo, playedFor, Beşiktaş Milangaz]
  • A. Besiktas JK chosen
    Beşiktaş JK is one of Turkey’s most prominent and historic multi-sport clubs, best known for its successful professional football team.
  • B. Galatasaray SK
    Galatasaray SK is a major Turkish multi-sport club best known for its successful football team, based in Istanbul.
  • C. Fenerbahce SK
    Fenerbahçe SK is one of Turkey’s most prominent multi-sport clubs, best known for its successful football team and large, passionate fan base.
  • D. Samsunspor
    Samsunspor is a professional Turkish sports club best known for its football team, based in the city of Samsun and competing in the national league system.
  • E. Bursaspor
    Bursaspor is a professional Turkish sports club best known for its football team, which has competed in the country’s top leagues and is based in the city of Bursa.
  • 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_69ab4955111c8190835bf619adec21ff completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd18fe32081909580c6272a6013c5 completed March 7, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f9111ec8190b464da14bc4be11e completed March 9, 2026, 7:29 p.m.
Created at: March 6, 2026, 9:45 p.m.