Triple
T3856167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surf's Up! |
E90019
|
entity |
| Predicate | nearbyResortSection |
P52374
|
FINISHED |
| Object | Touchdown! |
—
|
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: Touchdown! | Statement: [Surf's Up!, nearbyResortSection, Touchdown!]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyResortSection Context triple: [Surf's Up!, nearbyResortSection, Touchdown!]
-
A.
nearbyResortArea
Indicates that a resort area is located close to or within a short distance of a specified place or entity.
-
B.
associatedResort
Indicates a relationship where one entity is linked or connected to a specific resort, typically as its related or corresponding resort.
-
C.
notableResort
Indicates that a location functions as a resort that is recognized for its significance, prominence, or special reputation.
-
D.
resort
Indicates that one entity is used or turned to as a final or alternative option by another entity, often after other possibilities have been exhausted.
-
E.
hasSkiResortNearby
Indicates that one location is situated close enough to another location that it can be considered to have a ski resort in its vicinity.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec07d45081909b8f3e35eb710f4c |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aeeb828fb08190901d51edbe8bd304 |
completed | March 9, 2026, 3:47 p.m. |
Created at: March 9, 2026, 3:19 p.m.