Triple

T15829003
Position Surface form Disambiguated ID Type / Status
Subject Kazilik Koca Oglu Yigenek Boyu E383818 entity
Predicate protagonistIs P32529 FINISHED
Object Yigenek E1178974 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: Yigenek | Statement: [Kazilik Koca Oglu Yigenek Boyu, protagonistIs, Yigenek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yigenek
Context triple: [Kazilik Koca Oglu Yigenek Boyu, protagonistIs, Yigenek]
  • A. Yigenek chosen
    Yigenek is a heroic figure from the Turkic epic tradition, celebrated for his bravery and central role in the tales of the Book of Dede Korkut.
  • B. Yekini
    Yekini is the surname of Rashidi Yekini, the legendary Nigerian footballer best known as his country's all-time leading goal scorer.
  • C. Yunak
    Yunak is a rural district and town in Turkey known for its agricultural economy and location within the Central Anatolia region.
  • D. Enying
    Enying is a small town in central Hungary known for its agricultural surroundings and location within Fejér County.
  • E. Yagon
    Yagon is a coastal camping and recreation area within New South Wales’ Myall Lakes National Park, known for its beaches, dunes, and bushland setting.
  • 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_69d86da34c888190976e06c4019d415a completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e11e62aba8819090978801f4df73fe completed April 16, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa135be84819084f7c20c2bc01b47 completed May 9, 2026, 9:03 p.m.
Created at: April 10, 2026, 4:49 a.m.