Triple
T14733478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kodaira |
E346139
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Fuchu, 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: Fuchu, Tokyo | Statement: [Kodaira, borderedBy, Fuchu, Tokyo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fuchu, Tokyo Context triple: [Kodaira, borderedBy, Fuchu, Tokyo]
-
A.
Fuchu, Tokyo
chosen
Fuchu, Tokyo is a city in western Tokyo Metropolis known for its blend of residential suburbs, historical sites, and major facilities such as racetracks and large cemeteries.
-
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.
Musashino, Tokyo
Musashino, Tokyo is a suburban city in western Tokyo Metropolis known for its residential neighborhoods, parks, and several universities and cultural institutions.
-
D.
Chofu, Tokyo
Chofu, Tokyo is a suburban city in western Tokyo known for its residential neighborhoods, film and animation studios, and Chofu Airport.
-
E.
Tachikawa, Tokyo
Tachikawa, Tokyo is a major commercial and transportation hub in western Tokyo known for its busy shopping districts, business centers, and access to large parks and surrounding suburbs.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec72ea9348190817efcdaa973d7f7 |
completed | April 14, 2026, 11:01 p.m. |
Created at: April 10, 2026, 1:29 a.m.