Triple

T2632456
Position Surface form Disambiguated ID Type / Status
Subject Western Georgia E59664 entity
Predicate hasHistoricCity P3786 FINISHED
Object Kutaisi E7705 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: Kutaisi | Statement: [Western Georgia, hasHistoricCity, Kutaisi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kutaisi
Context triple: [Western Georgia, hasHistoricCity, Kutaisi]
  • A. Kutaisi chosen
    Kutaisi is one of Georgia’s major cities, historically significant and formerly a capital, located in the western part of the country.
  • B. Kuta
    Kuta is a popular beach resort town in southern Bali, Indonesia, known for its surfing waves, vibrant nightlife, and dense concentration of hotels, shops, and restaurants.
  • C. Kasoa
    Kasoa is a rapidly growing urban town in southern Ghana that serves as a major residential and commercial hub on the outskirts of Accra.
  • D. Hatta
    Hatta is an Indonesian surname most prominently associated with Mohammad Hatta, the country’s first vice president and a leading figure in the struggle for independence.
  • E. Kut
    Kut is a city in eastern Iraq situated on the banks of the Tigris River, known historically as a strategic location and the site of significant World War I battles.
  • 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8c8d32c819081fc89b91217ed54 completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98b93a108190b21f4af3e8c16c2b completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:50 p.m.