Triple

T15336098
Position Surface form Disambiguated ID Type / Status
Subject Bunkyō City E366668 entity
Predicate contains P35 FINISHED
Object Koishikawa district NE NERFINISHED

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: Koishikawa district | Statement: [Bunkyō City, contains, Koishikawa district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koishikawa district
Context triple: [Bunkyō City, contains, Koishikawa district]
  • A. Koishikawa district chosen
    Koishikawa district is a residential and educational neighborhood in Tokyo known for sites like Koishikawa Kōrakuen Garden and the University of Tokyo facilities.
  • B. Ueno district
    Ueno district is a cultural and historical area in Tokyo known for its major museums, temples, and the expansive Ueno Park.
  • C. Komagome district
    Komagome district is a residential and commercial neighborhood in Tokyo, Japan, known for its traditional atmosphere, historic temples, and proximity to Rikugien Garden.
  • D. Omotesando district
    Omotesando district is a fashionable Tokyo neighborhood known for its tree-lined avenue, high-end boutiques, modern architecture, and trendy cafes.
  • E. Nagatachō district
    Nagatachō district is Tokyo’s political center, housing key institutions such as the National Diet Building, the Prime Minister’s Office, and various government ministries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e03c5f081908e4d14dbdbc7f7a6 completed April 16, 2026, 1:40 a.m.
Created at: April 10, 2026, 3:17 a.m.