Triple

T14577429
Position Surface form Disambiguated ID Type / Status
Subject Akita Airport E342090 entity
Predicate cityServed P82 FINISHED
Object Akita E61829 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: Akita | Statement: [Akita Airport, cityServed, Akita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akita
Context triple: [Akita Airport, cityServed, Akita]
  • A. Akita chosen
    Akita is a city in Japan’s Tōhoku region, serving as the capital of Akita Prefecture and known for its port, rice production, and traditional festivals.
  • B. Akita
    Akita is a large, powerful Japanese dog breed known for its loyalty, dignity, and strong protective instincts.
  • C. Shiba
    Shiba is a central district in Minato, Tokyo, known for its mix of historic temples, business centers, and residential areas.
  • D. Ebisu
    Ebisu is a fashionable Tokyo neighborhood known for its upscale dining, craft beer scene, and convenient access via Ebisu Station near Shibuya.
  • E. Ebisu
    Ebisu is a popular Japanese kami of prosperity, fishermen, and good fortune, often depicted as a cheerful, bearded man holding a fishing rod and sea bream.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3f5ec448190b2ef887fdf7b633e completed April 14, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ace7da48190880a736ead5c4055 completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:24 a.m.