Triple

T6640625
Position Surface form Disambiguated ID Type / Status
Subject Nekresi Monastery E150576 entity
Predicate nearbyCity P350 FINISHED
Object Kvareli E148498 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: Kvareli | Statement: [Nekresi Monastery, nearbyCity, Kvareli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kvareli
Context triple: [Nekresi Monastery, nearbyCity, Kvareli]
  • A. Kvareli chosen
    Kvareli is a town in eastern Georgia’s Kakheti region, known for its wine production, historic fortress, and scenic location in the Alazani Valley near the Caucasus Mountains.
  • B. Dusheti
    Dusheti is a small historic town in eastern Georgia known for its mountainous surroundings and traditional architecture.
  • C. Tskhumi
    Tskhumi is the historical name of the city now known as Sukhumi, a major Black Sea port and the capital of the disputed region of Abkhazia.
  • D. Tavaeli
    Tavaeli is a regional dialect of the Kaili language spoken by communities in Central Sulawesi, Indonesia.
  • E. Ambrolauri
    Ambrolauri is a small town in western Georgia that serves as the administrative center of the Racha region, known for its mountainous scenery and local wine production.
  • 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_69c687f1a3048190828b7342f7125d5c completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aff42c748190b818cf55f83647cb completed March 27, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbf71874819080cc89b6740b1567 completed March 27, 2026, 6:27 p.m.
Created at: March 27, 2026, 2 p.m.