Triple

T22181608
Position Surface form Disambiguated ID Type / Status
Subject Hanwha Defense E548181 entity
Predicate headquartersLocation P62 FINISHED
Object Changwon NE NERFINISHED

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: Changwon | Statement: [Hanwha Defense, headquartersLocation, Changwon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changwon
Context triple: [Hanwha Defense, headquartersLocation, Changwon]
  • A. Changwon chosen
    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.
  • B. Ulsan
    Ulsan is a major industrial city in southeastern South Korea, known for its large automobile, shipbuilding, and petrochemical complexes.
  • C. Gunsan
    Gunsan is a coastal city in North Jeolla Province, South Korea, known for its port, industrial facilities, and longstanding association with nearby military air operations.
  • D. Busan
    Busan is South Korea’s second-largest city and a major international port known for its bustling harbor, beaches, and coastal scenery.
  • E. Gijeon
    Gijeon is an alternative name for the Seoul Capital Area, the densely populated metropolitan region surrounding South Korea’s capital city.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e3d53f88190a2b690e3f25bb062 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12aa5998081909ff35f8b5df4f92f completed April 28, 2026, 9:46 p.m.
Created at: April 16, 2026, 8:35 p.m.