Triple

T19444344
Position Surface form Disambiguated ID Type / Status
Subject Seoul Subway Line 2 E486432 entity
Predicate servesArea P82 FINISHED
Object Hongdae area 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: Hongdae area | Statement: [Seoul Subway Line 2, servesArea, Hongdae area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hongdae area
Context triple: [Seoul Subway Line 2, servesArea, Hongdae area]
  • A. Dongdaemun area
    The Dongdaemun area is a major commercial and cultural district in central Seoul, known for its large fashion markets, shopping complexes, and modern landmarks.
  • B. Ui-dong area
    Ui-dong area is a neighborhood in northern Seoul, South Korea, known for its residential character and improved accessibility via the Ui Light Rail Transit line.
  • C. Gwangalli neighborhood
    Gwangalli neighborhood is a coastal district in Busan, South Korea, known for its vibrant nightlife, cafes, and scenic views of Gwangandaegyo Bridge along the waterfront.
  • D. Hongdae chosen
    Hongdae is a vibrant neighborhood in Seoul known for its indie music scene, street art, nightlife, and youth culture centered around Hongik University.
  • E. Namsan area
    The Namsan area is a popular district in central Seoul known for Namsan Mountain, N Seoul Tower, scenic walking trails, and panoramic city views.
  • 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_69e63387e2048190bfb13fea434ddb46 completed April 20, 2026, 2:09 p.m.
Created at: April 10, 2026, 1:38 p.m.