Triple
T244510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuolumne County |
E5006
|
entity |
| Predicate | hasOutdoorActivity |
P971
|
FINISHED |
| Object | hiking |
—
|
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: hiking | Statement: [Tuolumne County, hasOutdoorActivity, hiking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOutdoorActivity Context triple: [Tuolumne County, hasOutdoorActivity, hiking]
-
A.
hasRecreationActivity
chosen
Indicates that an entity provides, includes, or is associated with a particular recreational activity.
-
B.
isOutdoorFacility
Indicates that a facility is located outdoors or primarily functions in an open-air environment.
-
C.
hasRecreationalArea
Indicates that an entity includes, provides, or is associated with a designated space intended for leisure or recreational activities.
-
D.
hasCampground
Indicates that one entity provides, contains, or is associated with a campground facility or area for another entity.
-
E.
hasMountainScenery
Indicates that a place or area features views or landscapes dominated by mountains.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b62839c8190824064fe5da6a92a |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.