Triple

T8622352
Position Surface form Disambiguated ID Type / Status
Subject Kutaisi International Airport E204196 entity
Predicate nearbyCity P350 FINISHED
Object Tskaltubo E99976 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: Tskaltubo | Statement: [Kutaisi International Airport, nearbyCity, Tskaltubo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tskaltubo
Context triple: [Kutaisi International Airport, nearbyCity, 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 (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_69ca834a4ea0819094970dceb9e389f3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4717f0e88190aaf0fd45bf726941 completed March 31, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebbdd6aac819091f6dd12815c3d94 completed April 2, 2026, 6:56 p.m.
Created at: March 30, 2026, 6:26 p.m.