Triple

T3709101
Position Surface form Disambiguated ID Type / Status
Subject Mtatsminda district E80963 entity
Predicate partOf P40 FINISHED
Object central Tbilisi 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: central Tbilisi | Statement: [Mtatsminda district, partOf, central Tbilisi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: central Tbilisi
Context triple: [Mtatsminda district, partOf, central Tbilisi]
  • 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. Marneuli
    Marneuli is a town in southern Georgia known for its ethnically diverse population, particularly its large Azerbaijani community, and its role as an agricultural and regional trade center.
  • C. 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.
  • D. Zugdidi
    Zugdidi is a city in western Georgia that serves as the main urban and administrative center of the Samegrelo region.
  • E. Rustavi
    Rustavi is an industrial city in southeastern Georgia, located near the capital Tbilisi and known for its steel production and Soviet-era urban planning.
  • 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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc58233788190be3b912a50f61443 completed March 8, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4ce0216bc8190b44d2950b7cb24c3 completed March 14, 2026, 2:54 a.m.
Created at: March 8, 2026, 3:33 p.m.