Triple

T19995752
Position Surface form Disambiguated ID Type / Status
Subject 早稲田大学大学院法学研究科 E494187 entity
Predicate prefecture P7509 FINISHED
Object 東京都 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: 東京都 | Statement: [早稲田大学大学院法学研究科, prefecture, 東京都]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 東京都
Context triple: [早稲田大学大学院法学研究科, prefecture, 東京都]
  • A. Tokyo Prefecture
    Tokyo Prefecture is Japan’s capital metropolitan region, encompassing the city of Tokyo and serving as the country’s political, economic, and cultural center.
  • B. Tōkyō-wan
    Tōkyō-wan is the Japanese name for Tokyo Bay, a major urban bay on the Pacific coast of Honshu that serves as a key economic and transportation hub for the Greater Tokyo Area.
  • C. Tokyo
    "Tokyo" is a popular Afrobeats song by Ghanaian singer King Promise featuring Nigerian artist Wizkid.
  • D. Tokyo chosen
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • E. Tokio
    Tokio is a popular asynchronous runtime for the Rust programming language, providing event-driven, non-blocking I/O for building high-performance network and concurrent applications.
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e65fe3fb288190a935c334e8a5d54e completed April 20, 2026, 5:18 p.m.
Created at: April 11, 2026, 3:32 p.m.