Triple
T16735872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabeguache Peak |
E406714
|
entity |
| Predicate | hasSeasonalAccessIssues |
P15928
|
FINISHED |
| Object | snow conditions |
—
|
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: snow conditions | Statement: [Tabeguache Peak, hasSeasonalAccessIssues, snow conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalAccessIssues Context triple: [Tabeguache Peak, hasSeasonalAccessIssues, snow conditions]
-
A.
hasSeasonalStatus
chosen
Indicates that an entity’s status, availability, or condition varies according to a particular season or time of year.
-
B.
hasSeasonalEvents
Indicates that an entity organizes or experiences events that occur only during specific seasons or times of the year.
-
C.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
D.
hasSeasonalParticipationIn
Indicates that an entity takes part in or is involved with another entity only during specific seasons or recurring seasonal periods.
-
E.
hasSeasonalHighlight
Indicates that something features a notable or emphasized aspect during a particular season or time of year.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c39c570819088723d59242c5c5c |
completed | April 18, 2026, 2:59 p.m. |
| PD | Predicate disambiguation | batch_69e319c807788190901250ab6e0ca55f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:20 a.m.