Triple

T6547073
Position Surface form Disambiguated ID Type / Status
Subject Ueno E151036 entity
Predicate hasLandmark P105 FINISHED
Object Ueno Zoo E213021 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: Ueno Zoo | Statement: [Ueno, hasLandmark, Ueno Zoo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ueno Zoo
Context triple: [Ueno, hasLandmark, Ueno Zoo]
  • A. Ueno Zoo chosen
    Ueno Zoo is a historic and popular zoological garden in Tokyo, Japan, renowned for its diverse animal collection and giant pandas.
  • B. Ueno Park
    Ueno Park is a large public park in Tokyo famous for its cherry blossoms, cultural institutions like museums and a zoo, and historic temples and shrines.
  • C. Tennoji Zoo
    Tennoji Zoo is a historic zoological park in Osaka, Japan, known for its diverse animal exhibits and location within the popular Tennoji district.
  • D. Shinagawa Aquarium
    Shinagawa Aquarium is a popular public aquarium in Tokyo known for its marine life exhibits and dolphin and sea lion shows.
  • E. Sumida Aquarium
    Sumida Aquarium is a modern indoor aquarium in Tokyo known for its innovative exhibits, including large open tanks and a focus on local aquatic life, located within the Tokyo Skytree Town complex.
  • 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_69c687f3fd60819083bfa583e5bcfa71 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6adf00aa48190a86a9ad4795363d9 completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e41f1eb8819086d0094015bdc1af completed March 27, 2026, 8:10 p.m.
Created at: March 27, 2026, 1:50 p.m.