Triple
T11221107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ōu Main Line |
E265563
|
entity |
| Predicate | connectsCity |
P4245
|
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: [Ōu Main Line, connectsCity, Akita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akita Context triple: [Ōu Main Line, connectsCity, Akita]
-
A.
Akita
Akita is a large, powerful Japanese dog breed known for its loyalty, dignity, and strong protective instincts.
-
B.
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.
-
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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8eb84c48190b4f3bede254afde2 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4977cab4481909c6b94ca07cd5e4a |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 8, 2026, 9:30 p.m.