Triple

T9689064
Position Surface form Disambiguated ID Type / Status
Subject Kaminarimon E234490 entity
Predicate symbolOf P129 FINISHED
Object Asakusa E72187 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: Asakusa | Statement: [Kaminarimon, symbolOf, Asakusa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asakusa
Context triple: [Kaminarimon, symbolOf, Asakusa]
  • A. Asakusa chosen
    Asakusa is a historic district in Tokyo best known for its ancient Sensō-ji Temple, traditional shopping streets, and preserved old-town atmosphere.
  • B. Asakusa district
    Asakusa district is a historic neighborhood in Tokyo best known for its ancient Sensō-ji Temple, traditional shopping streets, and preserved old-town atmosphere.
  • C. Komagome
    Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
  • D. Kamitabashi
    Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
  • E. Nishitokyo
    Nishitokyo is a suburban city in western Tokyo, Japan, known primarily as a residential area within the Tokyo metropolitan region.
  • 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_69ca84ca73208190957a900c8543bdcc completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d019d40819095059a4d6167900a completed April 1, 2026, 10:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95e38789881909e45e8d0b0489a59 completed April 10, 2026, 8:31 p.m.
Created at: March 30, 2026, 8:17 p.m.