Triple
T7345430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rowsley |
E169364
|
entity |
| Predicate | hasNearbyWalkingRoutes |
P76707
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Rowsley, hasNearbyWalkingRoutes, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyWalkingRoutes Context triple: [Rowsley, hasNearbyWalkingRoutes, true]
-
A.
hasWalkingRouteType
Indicates that an entity is associated with a specific type or category of walking route (e.g., trail, path, or walking itinerary).
-
B.
nearbyTransit
Indicates that one location has public transportation options situated within a short distance or easy access from it.
-
C.
hasWalkingPathAround
Indicates that one entity has a walking path that encircles or runs around another entity.
-
D.
hasNearbyCycleRoute
Indicates that an entity is located close to a designated cycling route or path.
-
E.
hasApproximateWalkingTimeTo
Indicates that there is an estimated or approximate amount of time it takes to walk from one entity to another.
- F. None of above. chosen
Provenance (4 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_69c68a57710481909f0c1f3c6ebdb6f2 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f139505c8190a7158cf59a6e089e |
completed | March 27, 2026, 9:06 p.m. |
| PD | Predicate disambiguation | batch_69c6f02aeeb8819099d1626566cec18b |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1379cac81908b35e617c44c7b13 |
completed | March 27, 2026, 9:05 p.m. |
Created at: March 27, 2026, 3:05 p.m.