Triple
T28620831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peru, Massachusetts |
E724378
|
entity |
| Predicate | recreationCharacteristic |
P112901
|
FINISHED |
| Object | outdoor recreation opportunities |
—
|
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 opportunities | Statement: [Peru, Massachusetts, recreationCharacteristic, outdoor recreation opportunities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recreationCharacteristic Context triple: [Peru, Massachusetts, recreationCharacteristic, outdoor recreation opportunities]
-
A.
hasRecreationalAspect
chosen
Indicates that something includes, involves, or is characterized by a recreational or leisure-related component or purpose.
-
B.
recreationUseLevel
Indicates the intensity or degree to which an entity is used for recreational activities.
-
C.
recreationLocation
Indicates the place where a recreational activity or leisure pursuit occurs.
-
D.
recreationActivitiesSupported
Indicates that an entity provides, allows, or is compatible with certain recreational activities.
-
E.
recreationSetting
Indicates the type of environment or context in which a recreational activity takes place.
- 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_69f01d822ac08190932de59ec2268ed2 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f65876c52c8190bc889c7a67bd07f3 |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 4:33 a.m.