Triple
T28051676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lehigh Canal |
E708838
|
entity |
| Predicate | towpathUsedFor |
P156755
|
FINISHED |
| Object | bicycling |
—
|
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: bicycling | Statement: [Lehigh Canal, towpathUsedFor, bicycling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: towpathUsedFor Context triple: [Lehigh Canal, towpathUsedFor, bicycling]
-
A.
hasTowpath
Indicates that a waterway or canal is accompanied by a path running alongside it, typically used for towing boats.
-
B.
rightOfWayUsedFor
Indicates that a particular right of way is utilized for a specific purpose, activity, or type of use.
-
C.
trailUses
chosen
Indicates that a trail supports or is designated for specific types of use or activities (such as hiking, biking, or horseback riding).
-
D.
numberOfTowpaths
Indicates the quantity of towpaths associated with or present along a given entity or feature.
-
E.
someRightOfWayUsedBy
Indicates that a particular right of way is utilized or traversed by a specified user, route, or transport 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_69ef9b6df9f48190bbb971d02cbe1b65 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f643ed0b7481908cf25f3afec0a61d |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641def1e88190a05bf865ced78b23 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 8:33 p.m.