Triple
T37864748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 嵐電（京福電気鉄道嵐山本線） |
E944439
|
entity |
| Predicate | 沿線名所 |
P10233
|
FINISHED |
| Object | 嵐山 |
—
|
NE NERFINISHED |
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: 嵐山 | Statement: [嵐電（京福電気鉄道嵐山本線）, 沿線名所, 嵐山]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 沿線名所 Context triple: [嵐電（京福電気鉄道嵐山本線）, 沿線名所, 嵐山]
-
A.
notableSpot
Indicates that a location is recognized as a significant or noteworthy place in some context.
-
B.
typicalSights
Indicates that certain sights or visual features are commonly or characteristically observed in association with a given entity or context.
-
C.
notablePlace
chosen
Indicates that a place is especially significant, famous, or noteworthy in relation to the subject.
-
D.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
-
E.
isScenicStartingPointFor
Indicates that a location serves as an especially picturesque or visually appealing starting point for a route, journey, or activity.
- F. None of above.
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_69f76eee2f9c8190b1272aa2ee55ebf5 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbae559a8819086ef839973f8d9b2 |
completed | May 6, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69fbb1440fa08190abf25ba684f75b6e |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.