Triple
T3510151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canal de Garonne |
E74175
|
entity |
| Predicate | towpathUse |
P13660
|
FINISHED |
| Object | cycling |
—
|
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: cycling | Statement: [Canal de Garonne, towpathUse, cycling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: towpathUse Context triple: [Canal de Garonne, towpathUse, cycling]
-
A.
hasTowpath
Indicates that a waterway or canal is accompanied by a path running alongside it, typically used for towing boats.
-
B.
roadUse
Indicates that an entity utilizes or travels on a particular road or roadway for movement or transport.
-
C.
someRightOfWayUsedBy
chosen
Indicates that a particular right of way is utilized or traversed by a specified user, route, or transport entity.
-
D.
bicycleUse
Indicates that an entity makes use of a bicycle for transportation, activity, or other purposes.
-
E.
usedTransportationInfrastructure
Indicates that an entity made use of some form of transportation infrastructure (such as roads, railways, or ports) to enable movement or transit.
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc0e1f0c8190b054d9fba16ce4b3 |
completed | March 8, 2026, 6:12 p.m. |
| PD | Predicate disambiguation | batch_69adae0e770481908528fa35eda53003 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:18 p.m.