Triple

T1883949
Position Surface form Disambiguated ID Type / Status
Subject Newport E39916 entity
Predicate hasTwinning P919 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: [Newport, hasTwinning, Kutaisi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kutaisi
Context triple: [Newport, hasTwinning, 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_69a88633e4fc8190b7eb40463e048ec5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb11d3cd48190bbd3ef2cf62e0dff completed March 7, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6ae4225081909ea0e59a5885cfc3 completed March 9, 2026, 6:38 a.m.
Created at: March 4, 2026, 7:34 p.m.