Triple

T12000381
Position Surface form Disambiguated ID Type / Status
Subject Busan Jung District E285640 entity
Predicate hasLandmark P105 FINISHED
Object Busan Tower E617928 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: Busan Tower | Statement: [Busan Jung District, hasLandmark, Busan Tower]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Busan Tower
Context triple: [Busan Jung District, hasLandmark, Busan Tower]
  • A. Busan Tower chosen
    Busan Tower is a prominent observation tower in Busan, South Korea, offering panoramic views of the city and its harbor.
  • B. N Seoul Tower
    N Seoul Tower is a prominent communication and observation tower on Namsan Mountain that serves as one of Seoul’s most recognizable cityscape landmarks and tourist attractions.
  • C. Kyobo Tower, Seoul
    Kyobo Tower in Seoul is a prominent modern office and commercial building best known as a landmark work of Swiss architect Mario Botta.
  • D. Posco Tower Seoul
    Posco Tower Seoul is a prominent skyscraper and corporate office building in Seoul, South Korea, serving as a major landmark and business hub in the city.
  • E. Jongno Tower
    Jongno Tower is a prominent high-rise office and commercial building in central Seoul, South Korea, known for its distinctive modern architecture and rooftop observatory.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903c26d7881909b67a31d04882eb5 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f48ae4733c81909956cc8d6bae343a completed May 1, 2026, 11:13 a.m.
Created at: April 8, 2026, 9:46 p.m.