Triple

T21721061
Position Surface form Disambiguated ID Type / Status
Subject Seoul Subway Line 1 E536155 entity
Predicate connects P390 FINISHED
Object Cheonan 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: Cheonan | Statement: [Seoul Subway Line 1, connects, Cheonan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cheonan
Context triple: [Seoul Subway Line 1, connects, Cheonan]
  • A. Cheonan chosen
    Cheonan is a major city in South Chungcheong Province, South Korea, known as a regional transportation hub and commercial center.
  • B. 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.
  • C. Jinju, South Korea
    Jinju, South Korea is a historic city in South Gyeongsang Province known for its riverside fortress, role in the Imjin War, and annual lantern festival.
  • D. Ulsan
    Ulsan is a major industrial city in southeastern South Korea, known for its large automobile, shipbuilding, and petrochemical complexes.
  • 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_69e0c46c6dd88190a595375fa6ebd701 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69efd96f1fbc8190a202f834aec1a319 completed April 27, 2026, 9:47 p.m.
Created at: April 16, 2026, 6:47 p.m.