Triple

T9413172
Position Surface form Disambiguated ID Type / Status
Subject Guri E226752 entity
Predicate hasRecreationalArea P5383 FINISHED
Object Guri Hangang Park E655060 NE FINISHED

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: Guri Hangang Park | Statement: [Guri, hasRecreationalArea, Guri Hangang Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guri Hangang Park
Context triple: [Guri, hasRecreationalArea, Guri Hangang Park]
  • A. Haga Park
    Haga Park is a historic royal park in the Stockholm area known for its landscaped grounds, cultural heritage sites, and recreational green spaces.
  • B. Daewangam Park
    Daewangam Park is a coastal park in Ulsan, South Korea, known for its dramatic seaside cliffs, pine forest trails, and views of the Daewangam Rock formation.
  • C. Baegun Lake Park
    Baegun Lake Park is a scenic lakeside recreational park in Uiwang, South Korea, known for its walking trails, waterfront views, and outdoor leisure facilities.
  • D. Taejongdae Park
    Taejongdae Park is a scenic coastal park in Busan, South Korea, famous for its dramatic seaside cliffs, lighthouse views, and walking trails overlooking the ocean.
  • E. Hangang Park chosen
    Hangang Park is a large network of riverside parks in Seoul, South Korea, popular for recreation, festivals, and scenic views along the Han River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca843280488190bc65600e843ef9e6 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd5258f7e081908d48600409181fdb completed April 1, 2026, 5:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12228d8148190814646881e1f2d98 completed April 4, 2026, 2:37 p.m.
Created at: March 30, 2026, 7:47 p.m.