Triple
T21665332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skyline Trail lookouts |
E534698
|
entity |
| Predicate | frequentWildlifeSightingsOf |
P111243
|
FINISHED |
| Object | moose |
—
|
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: moose | Statement: [Skyline Trail lookouts, frequentWildlifeSightingsOf, moose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentWildlifeSightingsOf Context triple: [Skyline Trail lookouts, frequentWildlifeSightingsOf, moose]
-
A.
typicalWildlifeObserved
chosen
Indicates that certain wildlife species are commonly or characteristically observed in a given area or context.
-
B.
hasNearbyWildlife
Indicates that there is wildlife located close to or in the immediate vicinity of the referenced entity.
-
C.
hasWildlifeActivity
Indicates that wildlife is present in the area and engaging in observable behaviors or movements.
-
D.
possibleSightings
Indicates that there are reported or potential observations of one entity by another or at a particular place or time.
-
E.
hasWildlifeIssue
Indicates that an entity is affected by, involved in, or responsible for a problem or conflict related to wildlife.
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0b26c8819092c13e59dcc3c25c |
completed | April 27, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:36 p.m.