Triple

T7255705
Position Surface form Disambiguated ID Type / Status
Subject Black Sea coast E157716 entity
Predicate hasMajorPort P942 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: [Black Sea coast, hasMajorPort, Batumi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Batumi
Context triple: [Black Sea coast, hasMajorPort, 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_69c6882d81d4819085f7ff862951ee4f completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6eaa0c76c81909fe43ed6938a13ea completed March 27, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db14f6c481908084aaa49d82787d completed March 28, 2026, 1:43 p.m.
Created at: March 27, 2026, 2:56 p.m.