Triple
T6389699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kameoka |
E143790
|
entity |
| Predicate | hasJapaneseName |
P9882
|
FINISHED |
| Object | 亀岡市 |
E143790
|
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: 亀岡市 | Statement: [Kameoka, hasJapaneseName, 亀岡市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 亀岡市 Context triple: [Kameoka, hasJapaneseName, 亀岡市]
-
A.
Hikone
Hikone is a historic city in Shiga Prefecture, Japan, best known for its well-preserved Hikone Castle overlooking Lake Biwa.
-
B.
Kameoka
chosen
Kameoka is a city in Kyoto Prefecture, Japan, known for its rural landscapes, historical sites, and proximity to Kyoto.
-
C.
Kōka, Shiga Prefecture
Kōka, Shiga Prefecture is a rural city in Japan’s Kansai region known for its historic ninja heritage and scenic mountain landscapes.
-
D.
Moriyama, Shiga
Moriyama, Shiga is a city in central Japan known for its location on the southeastern shore of Lake Biwa and its blend of residential, commercial, and historical areas.
-
E.
Kusatsu, Shiga
Kusatsu, Shiga is a city in Japan’s Kansai region known as a residential and commercial hub within the greater Kyoto–Osaka metropolitan area.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0686cc6d481909c62a29a84a4ce8e |
completed | March 22, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c638868d4481908611530d0bc8e286 |
completed | March 27, 2026, 7:57 a.m. |
Created at: March 22, 2026, 4:34 p.m.