Triple

T21697155
Position Surface form Disambiguated ID Type / Status
Subject Zugdidi railway station E535553 entity
Predicate locatedIn P40 FINISHED
Object Zugdidi NE NERFINISHED

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: Zugdidi | Statement: [Zugdidi railway station, locatedIn, Zugdidi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zugdidi
Context triple: [Zugdidi railway station, locatedIn, Zugdidi]
  • A. Zugdidi chosen
    Zugdidi is a city in western Georgia that serves as the main urban and administrative center of the Samegrelo region.
  • B. Tskhinvali
    Tskhinvali is the capital city of the breakaway region of South Ossetia in the South Caucasus, serving as its political and administrative center.
  • C. 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.
  • D. Zestafoni
    Zestafoni is a town in western Georgia known as an important industrial and transportation hub, particularly for its ferroalloy plant and railway connections.
  • 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 (2 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_69e0c46a6ee481908836e1420fb78c9b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef9b7b8da48190a863ac45eb4465a8 completed April 27, 2026, 5:23 p.m.
Created at: April 16, 2026, 6:45 p.m.