Triple

T10352269
Position Surface form Disambiguated ID Type / Status
Subject Honshu coast E243907 entity
Predicate hasMajorPortCity P2994 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: [Honshu coast, hasMajorPortCity, Akita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akita
Context triple: [Honshu coast, hasMajorPortCity, 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. Ekegusii
    Ekegusii is a Bantu language spoken primarily by the Abagusii people of western Kenya.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9489f9481908fc1c818e81c1cc2 completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7509c50d48190a567d9613a062efc completed April 9, 2026, 7:09 a.m.
Created at: April 6, 2026, 11:57 a.m.