Triple

T19117434
Position Surface form Disambiguated ID Type / Status
Subject U Line E467940 entity
Predicate localName P657 FINISHED
Object 의정부 경전철 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: 의정부 경전철 | Statement: [U Line, localName, 의정부 경전철]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 의정부 경전철
Context triple: [U Line, localName, 의정부 경전철]
  • A. Uijeongbu Light Rail Transit chosen
    Uijeongbu Light Rail Transit is an automated light metro system serving the city of Uijeongbu in Gyeonggi Province, South Korea.
  • B. Daejeon Metro
    Daejeon Metro is the urban rapid transit system serving the city of Daejeon in South Korea.
  • C. Gwangju Metro
    Gwangju Metro is the urban rapid transit system serving the city of Gwangju in South Korea.
  • D. Daegu Metro Line 1
    Daegu Metro Line 1 is a major rapid transit line in Daegu, South Korea, notable as the line on which the deadly 2003 Daegu subway fire occurred.
  • E. Daegu Metro Line 2
    Daegu Metro Line 2 is an east–west rapid transit line in Daegu, South Korea, forming a key part of the city's urban rail network.
  • 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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e399a6d8819090a9501ff1637b9d completed April 20, 2026, 8:28 a.m.
Created at: April 10, 2026, 12:05 p.m.