Triple

T4677102
Position Surface form Disambiguated ID Type / Status
Subject Kura E103707 entity
Predicate flowsThrough P225 FINISHED
Object Mingachevir E90695 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: Mingachevir | Statement: [Kura, flowsThrough, Mingachevir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mingachevir
Context triple: [Kura, flowsThrough, Mingachevir]
  • A. Mingachevir chosen
    Mingachevir is a city in Azerbaijan known for its large hydroelectric power station and reservoir on the Kura River, making it a key energy and industrial center in the country.
  • B. Abastumani
    Abastumani is a small resort town in southern Georgia, historically known for its mountain climate and therapeutic sanatoriums.
  • C. Akhaltsikhe
    Akhaltsikhe is a historic city in southern Georgia known for its multicultural heritage and the restored Rabati Castle complex.
  • D. Shuakhevi
    Shuakhevi is a small town and municipality in the mountainous region of Adjara in southwestern Georgia.
  • E. Khvanchkara
    Khvanchkara is a renowned semi-sweet red wine from Georgia, celebrated for its rich, fruity character and traditional production in the Racha region.
  • 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_69bd43dda32c8190938b37744ca270fc completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63698a548190831863adddd32f31 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03a0d5c88190a9b40e1ca7d165ff completed March 21, 2026, 2:34 a.m.
Created at: March 20, 2026, 1:16 p.m.