Triple

T7656277
Position Surface form Disambiguated ID Type / Status
Subject Tobu Skytree Line E173391 entity
Predicate serves P98 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: [Tobu Skytree Line, serves, Asakusa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asakusa
Context triple: [Tobu Skytree Line, serves, 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. Ueno
    Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
  • C. Ueno
    Ueno is a town in Japan historically known as the birthplace of the renowned haiku poet Matsuo Bashō.
  • D. Nagatacho
    Nagatacho is a central district in Tokyo, Japan, known as the political heart of the country and home to key government institutions such as the National Diet Building.
  • E. Fushimi
    Fushimi is a historic district in Kyoto, Japan, known for its castle and its association with key events and figures of the late Sengoku period.
  • 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_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7018fcbb48190a479f2effd939a8e completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9c2e6b2e88190be579a15109d4f82 completed March 30, 2026, 12:25 a.m.
Created at: March 27, 2026, 3:59 p.m.