Triple
T9981994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Trail (Staten Island Greenbelt) |
E196474
|
entity |
| Predicate | isRecreationType |
P3451
|
FINISHED |
| Object | outdoor recreation |
—
|
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: outdoor recreation | Statement: [Blue Trail (Staten Island Greenbelt), isRecreationType, outdoor recreation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRecreationType Context triple: [Blue Trail (Staten Island Greenbelt), isRecreationType, outdoor recreation]
-
A.
hasRecreationType
chosen
Indicates that an entity is associated with or offers a particular type or category of recreational activity.
-
B.
hasRecreationClassification
Indicates that an entity is assigned a specific type or category of recreational use or activity.
-
C.
hasRecreationPurpose
Indicates that something is used or intended to be used for recreational or leisure activities.
-
D.
supportsRecreationAt
Indicates that one entity provides facilities, conditions, or resources that enable recreational activities to take place at a specified location.
-
E.
hasRecreationDifficulty
Indicates the level of challenge or effort required to engage in a particular recreational activity or experience.
- 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_69ca82efbce081908179b4b9c65096eb |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb8bb3dc481909c65c37303e44037 |
completed | April 2, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9daa808190b413a1b9a1e929e2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:49 p.m.