Triple

T17867995
Position Surface form Disambiguated ID Type / Status
Subject Kumistavi village E446754 entity
Predicate hasNearbyCity P350 FINISHED
Object Tskaltubo NE NERFINISHED

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: Tskaltubo | Statement: [Kumistavi village, hasNearbyCity, Tskaltubo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tskaltubo
Context triple: [Kumistavi village, hasNearbyCity, Tskaltubo]
  • A. Tskaltubo chosen
    Tskaltubo is a spa town in western Georgia renowned for its radon-carbonate mineral springs and Soviet-era sanatoriums.
  • B. Borjomi
    Borjomi is a Georgian resort town famous for its mineral water springs and scenic location in the Borjomi Gorge.
  • C. Pyatigorsk
    Pyatigorsk is a historic spa and resort city in southern Russia, known for its mineral springs and location in the North Caucasus region.
  • D. Gudermes
    Gudermes is a town in the Chechen Republic of Russia that serves as an important regional transport and administrative center.
  • E. Mineralnye Vody
    Mineralnye Vody is a town in Russia’s Stavropol Krai known as a key transport hub in the North Caucasus, particularly for its railway and airport connections.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49aa0b69081909fba3b42d237b543 completed April 19, 2026, 9:04 a.m.
Created at: April 10, 2026, 10:17 a.m.