Triple
T16519806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 木曽川 |
E401286
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Kiso-gawa |
E479979
|
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: Kiso-gawa | Statement: [木曽川, hasAlternativeName, Kiso-gawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiso-gawa Context triple: [木曽川, hasAlternativeName, Kiso-gawa]
-
A.
Kisogawa
chosen
Kisogawa is the Japanese name for the Kiso River, a major river in central Honshu known for its scenic valleys and historical importance.
-
B.
Takinogawa
Takinogawa is a residential district in Kita Ward, Tokyo, known for its quiet neighborhoods and convenient urban access.
-
C.
Sakuragawa
Sakuragawa is a neighborhood in Osaka, Japan, known as one of the major districts within Naniwa Ward.
-
D.
Kizugawa
Kizugawa is a city in southern Kyoto Prefecture, Japan, known for its mix of historical sites, residential areas, and growing industrial and research facilities.
-
E.
Kizugawa
Kizugawa is a major district within Naniwa-ku in Osaka, Japan, known as part of the city's central urban 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e7f8a1481909fe6b3c16a72059b |
completed | April 18, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08cd41a5ec8190a477565ecbd83bf2 |
completed | May 16, 2026, 8:02 p.m. |
Created at: April 10, 2026, 5:14 a.m.