Triple
T37175688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Trail (Tobyhanna State Park) |
E921034
|
entity |
| Predicate | isRecreational |
P187506
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Red Trail (Tobyhanna State Park), isRecreational, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRecreational Context triple: [Red Trail (Tobyhanna State Park), isRecreational, yes]
-
A.
hasRecreationalAspect
Indicates that something includes, involves, or is characterized by a recreational or leisure-related component or purpose.
-
B.
hasRecreationalContext
Indicates that something occurs, is used, or is understood within a leisure, entertainment, or recreational setting or purpose.
-
C.
isRecreationalArea
Indicates that a place or space is designated and used primarily for leisure, relaxation, or recreational activities.
-
D.
isRecreationalGateway
Indicates that something serves as an entry point or access hub for recreational activities or leisure experiences.
-
E.
isRecreationalFacility
Indicates that the subject entity functions as a place or installation intended for leisure, sports, or other recreational activities.
- 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_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69fb55dc36d08190a0634fa680e13114 |
completed | May 6, 2026, 2:53 p.m. |
Created at: May 3, 2026, 4:15 p.m.