Triple

T6611568
Position Surface form Disambiguated ID Type / Status
Subject Didier Drogba E149249 entity
Predicate playedFor P2170 FINISHED
Object Galatasaray SK E30281 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: Galatasaray SK | Statement: [Didier Drogba, playedFor, Galatasaray SK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Galatasaray SK
Context triple: [Didier Drogba, playedFor, Galatasaray SK]
  • A. Galatasaray SK chosen
    Galatasaray SK is a major Turkish multi-sport club best known for its successful football team, based in Istanbul.
  • B. 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.
  • C. Besiktas JK
    Beşiktaş JK is one of Turkey’s most prominent and historic multi-sport clubs, best known for its successful professional football team.
  • D. MKE Ankaragücü
    MKE Ankaragücü is a professional Turkish sports club best known for its football team, traditionally representing the capital city Ankara in the country’s top leagues.
  • E. Kayserispor
    Kayserispor is a professional Turkish football club based in Kayseri that competes in the country’s top leagues.
  • 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_69c687ebc680819094caf71faba2efe2 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af3778a8819094e83afed7c6596f completed March 27, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e43f14148190882b9b8f2f95e22c completed March 27, 2026, 8:10 p.m.
Created at: March 27, 2026, 1:57 p.m.