Triple

T19449518
Position Surface form Disambiguated ID Type / Status
Subject Seoul Plaza E486576 entity
Predicate adjacentTo P224 FINISHED
Object Seoul City Hall Station 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: Seoul City Hall Station | Statement: [Seoul Plaza, adjacentTo, Seoul City Hall Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seoul City Hall Station
Context triple: [Seoul Plaza, adjacentTo, Seoul City Hall Station]
  • A. Seoul City Hall Station chosen
    Seoul City Hall Station is a major Seoul Metropolitan Subway hub located near Seoul City Hall and key downtown landmarks, serving as an important transfer and access point in the city center.
  • B. Seocho Station
    Seocho Station is a subway station in southern Seoul, South Korea, serving as a transit hub for commuters in the Seocho area.
  • C. Yongsan station
    Yongsan station is a major railway and subway hub in central Seoul, South Korea, serving high-speed, intercity, and commuter trains as well as multiple metro lines.
  • D. Seoul National University Station
    Seoul National University Station is a major Seoul Metropolitan Subway stop serving the area near Seoul National University in southern Seoul.
  • E. Gwanak Station
    Gwanak Station is a railway station in South Korea that serves the city of Anyang and connects it to the broader Seoul metropolitan 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6338caeb48190aeb1d511996984e3 completed April 20, 2026, 2:09 p.m.
Created at: April 10, 2026, 1:38 p.m.