Triple
T11161034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamiyama |
E264034
|
entity |
| Predicate | romanizedForm |
P2508
|
FINISHED |
| Object | Kamiyama |
E264034
|
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: Kamiyama | Statement: [Kamiyama, romanizedForm, Kamiyama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamiyama Context triple: [Kamiyama, romanizedForm, Kamiyama]
-
A.
Kamiyama
chosen
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
-
B.
Nagayama
Nagayama is a residential and commercial district within Tama New Town in Tokyo, Japan, known for its planned urban layout and local amenities.
-
C.
Oyamazaki
Oyamazaki is a town in Kyoto Prefecture, Japan, known for its historical significance and scenic location at the confluence of major rivers and transportation routes.
-
D.
Iwatsuki
Iwatsuki is a former city in Saitama Prefecture, Japan, now a ward of Saitama City known historically for its traditional doll-making industry.
-
E.
Wakamatsu
Wakamatsu is a ward in the city of Kitakyushu, Japan, known historically as a port and industrial area on the northern coast of Kyushu.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8817a90819087820d5241c58851 |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda8fd6f5081908de9a9e3df28a8ea |
completed | May 8, 2026, 9:12 a.m. |
Created at: April 8, 2026, 9:29 p.m.