Triple

T3225859
Position Surface form Disambiguated ID Type / Status
Subject Namba City E67619 entity
Predicate locatedIn P40 FINISHED
Object Chuo-ku, Osaka, Japan E260288 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: Chuo-ku, Osaka, Japan | Statement: [Namba City, locatedIn, Chuo-ku, Osaka, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chuo-ku, Osaka, Japan
Context triple: [Namba City, locatedIn, Chuo-ku, Osaka, Japan]
  • A. Abeno-ku, Osaka, Japan
    Abeno-ku is a central ward of Osaka, Japan, known as a major commercial and transportation hub that hosts the landmark skyscraper Abeno Harukas.
  • B. Yodogawa-ku, Osaka
    Yodogawa-ku, Osaka is a ward in northern Osaka City known as a major transportation hub, notably hosting Shin-Osaka Station, the city’s primary Shinkansen terminal.
  • C. Chuo-ku, Osaka chosen
    Chuo-ku, Osaka is a central ward of Osaka City known as a major commercial, business, and entertainment hub.
  • D. Konohana-ku, Osaka
    Konohana-ku, Osaka is a ward of Osaka City in Japan known for hosting major attractions like Universal Studios Japan and its themed entertainment areas.
  • E. Naniwa-ku, Osaka
    Naniwa-ku, Osaka is a central ward of Osaka City known for its busy commercial districts, entertainment areas, and major transport hubs such as Namba.
  • 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_69ad858c61888190a31196310d9b30b5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaeb4cd3481908af8a2c9b6c0742d completed March 8, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69bda3f5a8a88190a494a9338c01962a completed March 20, 2026, 7:45 p.m.
Created at: March 8, 2026, 3:08 p.m.