Triple

T36828118
Position Surface form Disambiguated ID Type / Status
Subject Beşiktaş J.K. (basketball) E910063 entity
Predicate represents P129 FINISHED
Object Beşiktaş multi-sport club
Beşiktaş multi-sport club is a major Turkish sports organization based in Istanbul, best known for its professional football team but also active in numerous other sports branches.
E2209672 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 multi-sport club | Statement: [Beşiktaş J.K. (basketball), represents, Beşiktaş multi-sport club]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Beşiktaş multi-sport club
Triple: [Beşiktaş J.K. (basketball), represents, Beşiktaş multi-sport club]
Generated description
Beşiktaş multi-sport club is a major Turkish sports organization based in Istanbul, best known for its professional football team but also active in numerous other sports branches.

Provenance (5 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_69f76e7e9d60819092442fba73290a46 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7cabbc1008190a77cf3b503edb7df completed May 3, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e57489a1c819087894d8730aefa22 completed June 26, 2026, 10:41 a.m.
NEDg Description generation batch_6a3e590379ec81908abaeb5d94e0a87a completed June 26, 2026, 10:48 a.m.
NED2 Entity disambiguation (via description) batch_6a3e848175bc8190965c8c71a1889cb9 completed June 26, 2026, 1:54 p.m.
Created at: May 3, 2026, 4:13 p.m.