Triple
T10939739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kagawa Prefecture |
E258435
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Sanuki |
E496372
|
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: Sanuki | Statement: [Kagawa Prefecture, hasCity, Sanuki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanuki Context triple: [Kagawa Prefecture, hasCity, Sanuki]
-
A.
Sanuki
chosen
Sanuki is a city in Kagawa Prefecture on Japan’s Shikoku island, known for its coastal scenery and association with Sanuki-style udon noodles.
-
B.
Kameyama
Kameyama is a city in Mie Prefecture, Japan, known historically as a post town on the Tōkaidō and for its preserved castle ruins and traditional streetscapes.
-
C.
Setouchi
Setouchi is a coastal town on Japan’s Amami Ōshima known for its subtropical climate, scenic bays, and traditional island culture.
-
D.
Fujinomiya
Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
-
E.
Ikawai
Ikawai is a small rural settlement in the Waimate District of the Canterbury region on New Zealand’s South Island.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770c1389881909341170984211810 |
completed | April 9, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49c59538081909102a6954f564e46 |
completed | May 1, 2026, 12:28 p.m. |
Created at: April 8, 2026, 9:23 p.m.