Triple
T28556999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teton Village, Wyoming |
E723033
|
entity |
| Predicate | hasSecondarySeason |
P135328
|
FINISHED |
| Object | summer |
—
|
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: summer | Statement: [Teton Village, Wyoming, hasSecondarySeason, summer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondarySeason Context triple: [Teton Village, Wyoming, hasSecondarySeason, summer]
-
A.
hasSeason
Indicates that an entity possesses, occurs during, or is associated with a particular season or set of seasons.
-
B.
hasSeasonalCounterpart
Indicates that one entity corresponds to another entity that appears or is relevant in a different season as its counterpart.
-
C.
hasSecondaryPeriod
chosen
Indicates that an entity is associated with an additional, subordinate, or second time period beyond its primary period.
-
D.
hasSeasonRelation
Indicates a relationship where one entity is associated with another through a specific season or seasonal context (e.g., occurring in, relevant to, or characteristic of that season).
-
E.
hasSeasonType
Indicates that something is associated with a particular category or type of season (e.g., summer, winter, rainy).
- 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_69f01a60204481909af1bb76247b8221 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: April 28, 2026, 3:46 a.m.