Triple
T14679639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kichijōji Station |
E344743
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Musashino, Tokyo |
—
|
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: Musashino, Tokyo | Statement: [Kichijōji Station, locatedIn, Musashino, Tokyo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Musashino, Tokyo Context triple: [Kichijōji Station, locatedIn, Musashino, Tokyo]
-
A.
Musashino, Tokyo
chosen
Musashino, Tokyo is a suburban city in western Tokyo Metropolis known for its residential neighborhoods, parks, and several universities and cultural institutions.
-
B.
Higashiyamato, Tokyo
Higashiyamato is a suburban city in western Tokyo, Japan, known for its residential neighborhoods, parks, and access via the Tama Monorail.
-
C.
Nakano, Tokyo
Nakano, Tokyo is a special ward in western Tokyo known for its dense residential neighborhoods, vibrant shopping streets, and pop culture hub around Nakano Broadway.
-
D.
Hachioji, Tokyo
Hachioji, Tokyo is a major suburban city in western Tokyo known for its residential areas, universities, and proximity to Mount Takao.
-
E.
Aoyama, Tokyo
Aoyama, Tokyo is an upscale neighborhood in Minato Ward known for its fashionable boutiques, trendy cafes, art galleries, and modern architecture.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb5692284819090f775be8e478522 |
completed | April 14, 2026, 9:45 p.m. |
Created at: April 10, 2026, 1:27 a.m.