Triple
T7805009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canada Water, London |
E180525
|
entity |
| Predicate | hasCyclingRoute |
P17835
|
FINISHED |
| Object | local cycle routes linking to Thames Path |
—
|
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: local cycle routes linking to Thames Path | Statement: [Canada Water, London, hasCyclingRoute, local cycle routes linking to Thames Path]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCyclingRoute Context triple: [Canada Water, London, hasCyclingRoute, local cycle routes linking to Thames Path]
-
A.
hasNearbyCycleRoute
Indicates that an entity is located close to a designated cycling route or path.
-
B.
hasRideCycle
Indicates that one entity is associated with, or participates in, a recurring sequence or cycle of rides or ride operations.
-
C.
hasRecreationalRoute
chosen
Indicates that an entity is associated with or includes a route intended for recreational activities such as walking, cycling, or hiking.
-
D.
hasCyclingDistance
Indicates that there is a specified distance associated with traveling between entities by cycling.
-
E.
hasBicycleFacilities
Indicates that appropriate bicycle-related infrastructure or amenities are available at or associated with the subject.
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:35 p.m.