Triple
T13336132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ichigaya district, Tokyo |
E317696
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Iidabashi |
—
|
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: Iidabashi | Statement: [Ichigaya district, Tokyo, locatedNear, Iidabashi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Iidabashi Context triple: [Ichigaya district, Tokyo, locatedNear, Iidabashi]
-
A.
Nishi-Tobecho
Nishi-Tobecho is a notable neighborhood within Nishi Ward in Yokohama, Japan, known as part of the city’s central urban area.
-
B.
Komagome
Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
-
C.
Toshima
Toshima is a small, sparsely populated volcanic island and village in Tokyo’s Izu Islands, known for its natural scenery and traditional rural lifestyle.
-
D.
Toshima
Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
-
E.
Asakusabashi
chosen
Asakusabashi is a district in Tokyo known for its traditional wholesale shops, craft stores, and convenient access to central city areas.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d00b75c8190af98784c7df904c8 |
completed | April 11, 2026, 12:59 a.m. |
Created at: April 9, 2026, 9:31 p.m.