Triple

T4653369
Position Surface form Disambiguated ID Type / Status
Subject Gonio Fortress E102348 entity
Predicate nearCity P350 FINISHED
Object Batumi E41677 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: Batumi | Statement: [Gonio Fortress, nearCity, Batumi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Batumi
Context triple: [Gonio Fortress, nearCity, Batumi]
  • A. Batumi chosen
    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.
  • B. Tbilisi
    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.
  • C. Zugdidi
    Zugdidi is a city in western Georgia that serves as the main urban and administrative center of the Samegrelo region.
  • D. Tskhinvali
    Tskhinvali is the capital city of the breakaway region of South Ossetia in the South Caucasus, serving as its political and administrative center.
  • 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_69bd43d71a308190afea7280841b0de8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6314883481908f085a7af497b0d8 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69be43936630819094417faf4df7f6df completed March 21, 2026, 7:06 a.m.
Created at: March 20, 2026, 1:14 p.m.