Triple

T10039090
Position Surface form Disambiguated ID Type / Status
Subject Dimlî E205248 entity
Predicate spokenIn P2266 FINISHED
Object Sivas Province E267227 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: Sivas Province | Statement: [Dimlî, spokenIn, Sivas Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sivas Province
Context triple: [Dimlî, spokenIn, Sivas Province]
  • A. Sivas Province chosen
    Sivas Province is a large, historically significant region in central Turkey known for its diverse ethnic makeup, including Zazaki-speaking communities, and its role as a cultural and transportation crossroads in Anatolia.
  • B. Muş Province
    Muş Province is an eastern Turkish province known for its mountainous terrain, harsh continental climate, and predominantly Kurdish population.
  • C. Elazığ Province
    Elazığ Province is an eastern Turkish province known for its significant Zaza-speaking population, rich Anatolian history, and mountainous landscapes.
  • D. Erzurum Province
    Erzurum Province is a large, historically significant region in eastern Turkey known for its mountainous terrain, harsh winters, and the city of Erzurum as its administrative center.
  • E. Bingöl Province
    Bingöl Province is an eastern Turkish province known for its mountainous landscape, Kurdish and Zaza populations, and rich local culture.
  • 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_69ca834f70e88190b2d74828b7767ec1 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcee04afc8190904704d66e23a432 completed April 2, 2026, 2:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3734e5e688190bbfa472547ef65e8 completed April 18, 2026, 12:04 p.m.
Created at: March 30, 2026, 8:55 p.m.