Triple

T13333525
Position Surface form Disambiguated ID Type / Status
Subject მცხეთა E317629 entity
Predicate nearbyCity P350 FINISHED
Object თბილისი E19766 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: თბილისი | Statement: [მცხეთა, nearbyCity, თბილისი]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: თბილისი
Context triple: [მცხეთა, nearbyCity, თბილისი]
  • A. Tbilisi chosen
    Tbilisi is the largest city and cultural, political, and economic center of Georgia, located on the banks of the Kura River in the South Caucasus.
  • B. Batumi
    Batumi is a major Black Sea resort city in southwestern Georgia known for its beaches, modern skyline, and role as a regional economic and cultural hub.
  • C. Zugdidi
    Zugdidi is a city in western Georgia that serves as the main urban and administrative center of the Samegrelo region.
  • D. Mtskheta
    Mtskheta is an ancient town in central Georgia and a UNESCO World Heritage Site, renowned as one of the country’s oldest continuously inhabited cities and a historic center of Georgian Christianity.
  • E. Telavi
    Telavi is a historic city in eastern Georgia known as the cultural and economic center of the Kakheti wine-producing 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99cff44e08190b9583baf0b626e42 completed April 11, 2026, 12:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f36e4cc819093007404ceb5da31 completed May 3, 2026, 10:11 a.m.
Created at: April 9, 2026, 9:30 p.m.