Triple
T20063549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kobe, Hyogo, Japan |
E499546
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Kitano-cho |
—
|
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: Kitano-cho | Statement: [Kobe, Hyogo, Japan, hasDistrict, Kitano-cho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kitano-cho Context triple: [Kobe, Hyogo, Japan, hasDistrict, Kitano-cho]
-
A.
Kitano-cho
chosen
Kitano-cho is a historic district in Kobe, Japan, known for its preserved Western-style residences built by foreign merchants in the late 19th and early 20th centuries.
-
B.
Haginochaya
Haginochaya is a neighborhood in Osaka’s Naniwa Ward known for its dense urban streetscape, budget accommodations, and proximity to major transit and entertainment areas.
-
C.
Matsuyamachi
Matsuyamachi is a traditional shopping district in central Osaka known for its long history of wholesale shops selling toys, dolls, and festival goods.
-
D.
Toyonaka
Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
-
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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66377b6b48190a0a37279f285123e |
completed | April 20, 2026, 5:33 p.m. |
Created at: April 11, 2026, 3:39 p.m.