Triple
T9248535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyoto Basin |
E222258
|
entity |
| Predicate | formsGeographicSettingFor |
P3227
|
FINISHED |
| Object | Nagaokakyo |
E135579
|
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: Nagaokakyo | Statement: [Kyoto Basin, formsGeographicSettingFor, Nagaokakyo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagaokakyo Context triple: [Kyoto Basin, formsGeographicSettingFor, Nagaokakyo]
-
A.
Nagaokakyo
chosen
Nagaokakyo is a suburban city in Japan known for its bamboo groves, historical temples, and convenient location between Kyoto and Osaka.
-
B.
Kamogawa
Kamogawa is a coastal city in Chiba Prefecture, Japan, known for its beaches, fishing industry, and the popular Kamogawa Sea World aquarium.
-
C.
Kamogawa
Kamogawa is a prominent river running through Kyoto, Japan, known for its scenic banks, cultural significance, and popular walking paths.
-
D.
Suruga Kanbaru
Suruga Kanbaru is a spirited, athletic high school girl and former basketball star from the Monogatari Series, known for her monkey’s paw curse, rapid-fire speech, and open admiration for her senior Hitagi Senjougahara.
-
E.
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.
- 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_69ca841d2b18819089f9faf5b2c2aec0 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd05f6d62c8190a1e33f1854767b47 |
completed | April 1, 2026, 11:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e4d5f5008190a897b3b10b172592 |
completed | April 5, 2026, 10:40 p.m. |
Created at: March 30, 2026, 7:31 p.m.