Triple

T15828987
Position Surface form Disambiguated ID Type / Status
Subject Bamsi Beyrek Boyu E383817 entity
Predicate relatedWork P37 FINISHED
Object Salur Kazan Boyu E1178971 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: Salur Kazan Boyu | Statement: [Bamsi Beyrek Boyu, relatedWork, Salur Kazan Boyu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salur Kazan Boyu
Context triple: [Bamsi Beyrek Boyu, relatedWork, Salur Kazan Boyu]
  • A. Salur Kazan chosen
    Salur Kazan is a legendary Oghuz Turkic hero and chieftain featured prominently in the medieval epic Book of Dede Korkut.
  • B. Kasplya
    Kasplya is a river in Eastern Europe that serves as a tributary of the Western Dvina (Daugava) River.
  • C. Yarbay
    Yarbay is a mid-level field officer rank in the Turkish Armed Forces, equivalent to a lieutenant colonel in many other military organizations.
  • D. Ozerki
    Ozerki is a locality in Russia historically noted as the site where the revolutionary priest Georgy Gapon was killed.
  • E. Yamskaya
    Yamskaya is a name element associated with several historic streets and districts in Moscow, traditionally linked to coachmen’s settlements along major travel routes.
  • 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_69ffa93be478819099908e7242f532d7 completed May 9, 2026, 9:38 p.m.
Created at: April 10, 2026, 4:49 a.m.