Triple
T10278859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itabashi, Tokyo |
E241039
|
entity |
| Predicate | hasFriendshipCity |
P9364
|
FINISHED |
| Object | Hakusan, Ishikawa |
E732536
|
NE FINISHED |
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: Hakusan, Ishikawa | Statement: [Itabashi, Tokyo, hasFriendshipCity, Hakusan, Ishikawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hakusan, Ishikawa Context triple: [Itabashi, Tokyo, hasFriendshipCity, Hakusan, Ishikawa]
-
A.
Hakusan, Ishikawa
chosen
Hakusan, Ishikawa is a city in Ishikawa Prefecture, Japan, known for its proximity to Mount Hakusan and rich Shinto heritage.
-
B.
Kusatsu
Kusatsu is a Japanese city in Shiga Prefecture known as a regional commercial hub and transportation crossroads near Lake Biwa.
-
C.
Kusatsu, Gunma
Kusatsu, Gunma is a renowned hot spring resort town in Gunma Prefecture, Japan, famous for its high-volume, highly acidic thermal waters and traditional onsen culture.
-
D.
Kusatsu, Shiga
Kusatsu, Shiga is a city in Japan’s Kansai region known as a residential and commercial hub within the greater Kyoto–Osaka metropolitan area.
-
E.
Koshigaya
Koshigaya is a suburban city in Japan known for its large shopping complexes and residential communities within the Greater Tokyo metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4dfbfa26c8190b536655d33112ddf |
completed | April 7, 2026, 10:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f8286b1881908b54037d1798f74a |
completed | April 9, 2026, 12:51 a.m. |
Created at: April 6, 2026, 11:38 a.m.