Triple

T15253044
Position Surface form Disambiguated ID Type / Status
Subject Ameya-Yokochō E364566 entity
Predicate locatedIn P40 FINISHED
Object Ueno 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: Ueno district | Statement: [Ameya-Yokochō, locatedIn, Ueno district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ueno district
Context triple: [Ameya-Yokochō, locatedIn, Ueno district]
  • A. Ueno district chosen
    Ueno district is a cultural and historical area in Tokyo known for its major museums, temples, and the expansive Ueno Park.
  • B. Koishikawa district
    Koishikawa district is a residential and educational neighborhood in Tokyo known for sites like Koishikawa Kōrakuen Garden and the University of Tokyo facilities.
  • C. 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.
  • D. Hibiya district
    Hibiya district is a central Tokyo area known for its business centers, government buildings, and the historic Hibiya Park near the Imperial Palace.
  • E. Tamagawa district
    Tamagawa district is a residential neighborhood in Setagaya, Tokyo, known for its riverside location along the Tama River and relatively tranquil urban atmosphere.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f728648190b2c86e4528542b65 completed April 15, 2026, 9:49 p.m.
Created at: April 10, 2026, 3:13 a.m.