Triple
T12832941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shijo-dori |
E306832
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Pontocho |
E65226
|
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: Pontocho | Statement: [Shijo-dori, near, Pontocho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pontocho Context triple: [Shijo-dori, near, Pontocho]
-
A.
Bouyon
Bouyon is a small rural commune in southeastern France, situated in the Alpes-Maritimes department of the Provence-Alpes-Côte d’Azur region.
-
B.
Benchoona
Benchoona is one of the principal summits in Ireland’s Twelve Bens mountain range in Connemara, County Galway.
-
C.
Peynet
Peynet is the surname of French illustrator Raymond Peynet, best known for his romantic "lovers" drawings that became iconic in mid-20th-century France.
-
D.
Ponto-chō
chosen
Ponto-chō is a historic, narrow alley in Kyoto famous for its traditional teahouses, geisha culture, and atmospheric nightlife along the Kamogawa River.
-
E.
Enchin
Enchin was a prominent 9th-century Japanese Tendai Buddhist monk and scholar who played a key role in the development of esoteric Buddhism in Japan.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96fb0bb208190bdc4d3dc7909be06 |
completed | April 10, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ed8d20081908e0fb5262b354cab |
completed | May 2, 2026, 11:55 p.m. |
Created at: April 9, 2026, 5:34 p.m.