Triple
T23469508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ningyōchō Station |
E569188
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ningyōchō |
—
|
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: Ningyōchō | Statement: [Ningyōchō Station, locatedIn, Ningyōchō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ningyōchō Context triple: [Ningyōchō Station, locatedIn, Ningyōchō]
-
A.
Ningyōchō
chosen
Ningyōchō is a traditional downtown neighborhood in Tokyo known for its old-style shops, restaurants, and remnants of the city’s Edo-period atmosphere.
-
B.
Bakurochō
Bakurochō is a commercial district in Tokyo known historically as a wholesale textile and clothing center with convenient access to major rail and transit lines.
-
C.
Shōji-ko
Shōji-ko is one of the Fuji Five Lakes in Yamanashi Prefecture, Japan, known for its scenic views of Mount Fuji and relatively undeveloped, tranquil surroundings.
-
D.
Shintomichō
Shintomichō is a neighborhood located within Tokyo’s central Chūō ward, known for its mix of residential and commercial urban streets.
-
E.
Kizoku-in
Kizoku-in was the upper house of Japan’s prewar Imperial Diet, composed mainly of nobility and imperial appointees.
- 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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a6feb5688190ad4ce42fc9590adb |
completed | April 29, 2026, 6:36 a.m. |
Created at: April 17, 2026, 5:54 p.m.