Triple

T19267815
Position Surface form Disambiguated ID Type / Status
Subject Wakakusa-yama E481834 entity
Predicate partOf P40 FINISHED
Object Nara Park 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: Nara Park area | Statement: [Wakakusa-yama, partOf, Nara Park area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nara Park area
Context triple: [Wakakusa-yama, partOf, Nara Park area]
  • A. Nara Park chosen
    Nara Park is a famous public park in Nara, Japan, known for its free-roaming deer and historic temples and shrines.
  • B. 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.
  • C. Yongin Daejanggeum Park
    Yongin Daejanggeum Park is a large historical drama filming set in Yongin, South Korea, known for recreating traditional Korean palaces and villages used in popular TV series.
  • D. Yongdusan Park
    Yongdusan Park is a popular hilltop park in Busan, South Korea, known for its scenic city and harbor views, walking paths, and the iconic Busan Tower.
  • E. 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.
  • 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_69d8e8ce54cc8190998418ff1f66ef28 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fb8e1f888190a95f60fa29ca3b98 completed April 20, 2026, 10:10 a.m.
Created at: April 10, 2026, 1:29 p.m.