Triple

T7313285
Position Surface form Disambiguated ID Type / Status
Subject Buk-gu, Ulsan E168146 entity
Predicate subdivisionName2 P766 FINISHED
Object Ulsan E28895 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: Ulsan | Statement: [Buk-gu, Ulsan, subdivisionName2, Ulsan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ulsan
Context triple: [Buk-gu, Ulsan, subdivisionName2, Ulsan]
  • A. Ulsan chosen
    Ulsan is a major industrial city in southeastern South Korea, known for its large automobile, shipbuilding, and petrochemical complexes.
  • B. Changwon
    Changwon is a major industrial and administrative city in South Gyeongsang Province, South Korea, known for its planned urban layout and role as a regional government and manufacturing hub.
  • C. Gijeon
    Gijeon is an alternative name for the Seoul Capital Area, the densely populated metropolitan region surrounding South Korea’s capital city.
  • D. Pohang
    Pohang is a major industrial and port city in South Korea, best known as the home of the global steelmaker POSCO and a key hub on the country’s east coast.
  • E. Daegu
    Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
  • 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_69c6888d8e3c81909db79714903baf31 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6ec02319c819096d25e3683943886 completed March 27, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525100e108190b4f6949695c7156e completed April 19, 2026, 6:55 p.m.
Created at: March 27, 2026, 3:02 p.m.