Triple
T11741806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 桂川 |
E279172
|
entity |
| Predicate | 交通との関係 |
P43050
|
FINISHED |
| Object | 保津川下り観光船が運航されている |
—
|
LITERAL 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: 保津川下り観光船が運航されている | Statement: [桂川, 交通との関係, 保津川下り観光船が運航されている]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 交通との関係 Context triple: [桂川, 交通との関係, 保津川下り観光船が運航されている]
-
A.
hasTransportationRelation
chosen
Indicates a relationship in which one entity provides, uses, is connected by, or is otherwise associated with a means or mode of transportation to another entity or location.
-
B.
transportationImpact
Indicates how one entity’s transportation-related activities or characteristics affect another entity or the surrounding environment.
-
C.
roadJunctionRelation
Indicates a spatial connection where two or more roads meet, intersect, or join at a junction.
-
D.
traffics
Indicates engaging in the buying, selling, or illicit trading of someone or something, typically as part of an ongoing commercial or criminal operation.
-
E.
transportationReference
Indicates that one entity serves as a reference or identifier for a specific mode, instance, or detail of transportation associated with another entity.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f191388190bd6ef7e80c41ca48 |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a813cc48190a3dfdc60e8af80ae |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.