Triple

T1638379
Position Surface form Disambiguated ID Type / Status
Subject Namba Marui E35410 entity
Predicate locatedIn P40 FINISHED
Object Namba E4490 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 | Statement: [Namba Marui, locatedIn, Namba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namba
Context triple: [Namba Marui, locatedIn, Namba]
  • A. Namba chosen
    Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
  • B. Numata
    Numata is a city in Gunma Prefecture, Japan, known as a gateway to the Mount Akagi and Oze National Park areas.
  • C. Kanuma
    Kanuma is a regional harvest festival celebrated mainly in Andhra Pradesh and Telangana as part of the multi-day Makar Sankranti festivities, focusing on cattle worship and agricultural prosperity.
  • D. Namaka
    Namaka is the smaller and inner of the two known moons orbiting the dwarf planet Haumea in the Kuiper Belt.
  • E. Namba Marui
    Namba Marui is a major Marui department store and shopping complex located in Osaka’s bustling Namba district, known for its fashion, dining, and entertainment options.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a1ac46081909f10e793898a9911 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58ddfdbc819096578412818fdfbf completed March 8, 2026, 11:09 a.m.
Created at: March 4, 2026, 7:28 p.m.