Triple

T19825374
Position Surface form Disambiguated ID Type / Status
Subject Lake Haruna E476309 entity
Predicate locatedNorthwestOf P6790 FINISHED
Object Tokyo 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: Tokyo | Statement: [Lake Haruna, locatedNorthwestOf, Tokyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo
Context triple: [Lake Haruna, locatedNorthwestOf, Tokyo]
  • A. Tokyo chosen
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • B. Tokyo
    "Tokyo" is a popular Afrobeats song by Ghanaian singer King Promise featuring Nigerian artist Wizkid.
  • C. 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.
  • D. 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.
  • E. TOKIO
    TOKIO is a Japanese pop-rock band and idol group formed under Johnny & Associates, known for performing music and appearing in various television variety shows.
  • 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_69d8e51c7c188190b926f3a2a7b5f881 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e656c9e7348190a569a40bd1fca6ba completed April 20, 2026, 4:39 p.m.
Created at: April 10, 2026, 1:50 p.m.