Triple
T14979452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biei |
E373536
|
entity |
| Predicate | hasOfficialName |
P66
|
FINISHED |
| Object | Biei Town |
E373536
|
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: Biei Town | Statement: [Biei, hasOfficialName, Biei Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biei Town Context triple: [Biei, hasOfficialName, Biei Town]
-
A.
Biei
chosen
Biei is a picturesque rural town in Hokkaido, Japan, famed for its rolling patchwork hills, flower fields, and scenic landscapes that attract photographers and tourists year-round.
-
B.
Nobeoka City
Nobeoka City is a coastal city in southeastern Kyushu, Japan, known for its chemical and electronics industries and scenic natural surroundings.
-
C.
Kanoya
Kanoya is a city in Kagoshima Prefecture on Japan’s Kyushu island, known as a regional center on the Ōsumi Peninsula with agricultural production and a former naval air base.
-
D.
Miyakonojo City
Miyakonojo City is a regional city in southern Japan known for its agriculture, livestock production, and location within Miyazaki Prefecture on the island of Kyushu.
-
E.
Kamaishi
Kamaishi is a coastal city in northeastern Japan known for its historic iron and steel industry and as a venue for the 2019 Rugby World Cup.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6fcebf481909f72cab577560d82 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56b25a808190b56f8ab3c506b771 |
completed | May 9, 2026, 3:45 p.m. |
Created at: April 10, 2026, 2:51 a.m.