Triple
T14437517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taitō ward |
E358002
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Ameya-Yokochō |
—
|
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: Ameya-Yokochō | Statement: [Taitō ward, contains, Ameya-Yokochō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ameya-Yokochō Context triple: [Taitō ward, contains, Ameya-Yokochō]
-
A.
Ameya-Yokochō
chosen
Ameya-Yokochō is a bustling open-air market street in Tokyo known for its dense concentration of shops, food stalls, and bargain goods.
-
B.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
C.
Shintomichō
Shintomichō is a neighborhood located within Tokyo’s central Chūō ward, known for its mix of residential and commercial urban streets.
-
D.
Shichirōji
Shichirōji is a seasoned, loyal samurai and former comrade of Kambei in Akira Kurosawa’s film "Seven Samurai," known for his calm demeanor and steadfast bravery.
-
E.
Hamamatsuchō
Hamamatsuchō is a business and transportation district in Tokyo known for its major train and monorail stations, office towers, and proximity to Tokyo Bay.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de914a45ec81909ab8ccf302047d7f |
completed | April 14, 2026, 7:11 p.m. |
Created at: April 10, 2026, 1:18 a.m.