Triple

T3014255
Position Surface form Disambiguated ID Type / Status
Subject Naniwa-ku E82297 entity
Predicate hasTransportHub P2413 FINISHED
Object Namba Station area E16052 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: Namba Station area | Statement: [Naniwa-ku, hasTransportHub, Namba Station area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namba Station area
Context triple: [Naniwa-ku, hasTransportHub, Namba Station area]
  • A. Tabata Station
    Tabata Station is a railway station in Tokyo, Japan, served by JR East and known as one of the stops on the busy Yamanote Line.
  • B. Hanzōmon area
    The Hanzōmon area is a central Tokyo district near the Imperial Palace, known for its government offices, media companies, and relatively quiet, upscale residential atmosphere.
  • C. Aoyama area
    The Aoyama area is an upscale Tokyo neighborhood known for its fashionable boutiques, contemporary architecture, and trendy cafes and galleries.
  • 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. Namba Station chosen
    Namba Station is one of Osaka’s major railway and subway terminals, serving as a key commercial and transportation hub in the city’s bustling Namba district.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a69e8148190a97507740c9d26a8 completed March 8, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1dea9a7c4819087fb6853d839fb1e completed March 11, 2026, 9:29 p.m.
Created at: March 8, 2026, 3 p.m.