Triple
T13265400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kashiwa |
E315909
|
entity |
| Predicate | adjacentToMunicipality |
P33892
|
FINISHED |
| Object | Nagareyama |
—
|
NE NERFINISHED |
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: Nagareyama | Statement: [Kashiwa, adjacentToMunicipality, Nagareyama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagareyama Context triple: [Kashiwa, adjacentToMunicipality, Nagareyama]
-
A.
Nagareyama
chosen
Nagareyama is a city in Chiba Prefecture, Japan, known as a residential suburb of the Tokyo metropolitan area with growing commuter access and family-oriented neighborhoods.
-
B.
Yoiyama
Yoiyama is the lively evening street festival held before the main Gion Matsuri parade in Kyoto, featuring illuminated festival floats, food stalls, and traditional music.
-
C.
Aobayama
Aobayama is a hilly, forested area in Sendai known for housing parts of Tohoku University and offering scenic views over the city.
-
D.
Shizunai
Shizunai was a former town in Hokkaido, Japan, known for its horse-breeding traditions and later incorporated into the town of Shinhidaka.
-
E.
Nagayama
Nagayama is a residential and commercial district within Tama New Town in Tokyo, Japan, known for its planned urban layout and local amenities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd4cb008190af99c4856e76ac08 |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:25 p.m.