Triple

T15794923
Position Surface form Disambiguated ID Type / Status
Subject ვაჟა-ფშაველა E382952 entity
Predicate deathPlace P21 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: [ვაჟა-ფშაველა, deathPlace, თბილისი]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: თბილისი
Context triple: [ვაჟა-ფშაველა, deathPlace, 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. Kabilasi
    Kabilasi is a municipality-level town located in southeastern Nepal’s Madhesh Province, near the border with India.
  • C. 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.
  • D. Zugdidi
    Zugdidi is a city in western Georgia that serves as the main urban and administrative center of the Samegrelo region.
  • E. 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.
  • 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_69d86da16e188190b89af699f1ed0bfe completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b4dc887081909d682ae153f06d97 completed April 16, 2026, 10:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffb038dac881909ede37fa7766a249 completed May 9, 2026, 10:07 p.m.
Created at: April 10, 2026, 4:48 a.m.