Triple
T11741677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Togetsukyo Bridge |
E279170
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Arashiyama |
E284987
|
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: Arashiyama | Statement: [Togetsukyo Bridge, locatedIn, Arashiyama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arashiyama Context triple: [Togetsukyo Bridge, locatedIn, Arashiyama]
-
A.
Arashiyama district
chosen
Arashiyama district is a scenic area on the western outskirts of Kyoto, Japan, famed for its bamboo groves, historic temples, and iconic Togetsukyo Bridge.
-
B.
Fushimi
Fushimi is a historic district in Kyoto, Japan, known for its castle and its association with key events and figures of the late Sengoku period.
-
C.
Midorigaoka
Midorigaoka is a residential neighborhood located within Tokyo's Meguro ward in Japan.
-
D.
Sakuragaokacho
Sakuragaokacho is a neighborhood in Tokyo’s Shibuya ward known for its urban atmosphere and proximity to Shibuya Station.
-
E.
Ueno
Ueno is a town in Japan historically known as the birthplace of the renowned haiku poet Matsuo Bashō.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f191388190bd6ef7e80c41ca48 |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f019d331888190866bdd04f6c73e08 |
completed | April 28, 2026, 2:22 a.m. |
Created at: April 8, 2026, 9:41 p.m.