Triple

T17377686
Position Surface form Disambiguated ID Type / Status
Subject Abcam E422482 entity
Predicate hasOfficeLocation P1268 FINISHED
Object Tokyo, Japan 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, Japan | Statement: [Abcam, hasOfficeLocation, Tokyo, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo, Japan
Context triple: [Abcam, hasOfficeLocation, Tokyo, Japan]
  • 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. Ōta, Tokyo
    Ōta, Tokyo is a large ward in southern Tokyo known for its mix of residential and industrial areas and for hosting Haneda Airport, one of Japan’s major international gateways.
  • 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. Chuo City, Tokyo
    Chuo City, Tokyo is a central ward of Tokyo known for its historic commercial districts like Nihonbashi and Ginza, serving as a major hub for finance, retail, and culture.
  • 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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a6ea56c8190b56d966ccf2c91f7 completed April 19, 2026, 2:14 a.m.
Created at: April 10, 2026, 5:45 a.m.