Triple

T1195450
Position Surface form Disambiguated ID Type / Status
Subject Shibuya Station E25657 entity
Predicate hasNearbyLandmark P2064 FINISHED
Object Shibuya Stream E28885 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: Shibuya Stream | Statement: [Shibuya Station, hasNearbyLandmark, Shibuya Stream]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shibuya Stream
Context triple: [Shibuya Station, hasNearbyLandmark, Shibuya Stream]
  • A. Shibuya Stream chosen
    Shibuya Stream is a large mixed-use complex in Tokyo’s Shibuya district, featuring offices, shops, restaurants, and public spaces integrated with the area’s major transportation hub.
  • B. Sumida
    Sumida is a special ward in Tokyo, Japan, known for landmarks such as the Tokyo Skytree and its traditional shitamachi neighborhoods.
  • C. Nadi–Tokyo
    Nadi–Tokyo is an international flight route linking Nadi, Fiji with Tokyo, Japan, serving as a key air connection between the South Pacific and East Asia.
  • D. Toyonaka
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • E. Nagaokakyo
    Nagaokakyo is a suburban city in Japan known for its bamboo groves, historical temples, and convenient location between Kyoto and Osaka.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd78f61c8190bdba2255d35a8fe4 completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8f6ff3048190a420ee6c92fc9c71 completed March 7, 2026, 8:49 p.m.
Created at: March 1, 2026, 7:46 p.m.