Triple
T25780029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paso de Mahoma |
E649260
|
entity |
| Predicate | snowAndIcePossible |
P120545
|
FINISHED |
| Object | yes, especially early season |
—
|
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: yes, especially early season | Statement: [Paso de Mahoma, snowAndIcePossible, yes, especially early season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: snowAndIcePossible Context triple: [Paso de Mahoma, snowAndIcePossible, yes, especially early season]
-
A.
hasSnowAndIce
Indicates that the subject is covered with or contains both snow and ice.
-
B.
hasSnowRisk
chosen
Indicates that there is a potential or likelihood of snow affecting the related entity or situation.
-
C.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
D.
hasSnowIn
Indicates that snow is present or occurs within a specified location or region.
-
E.
hasWinterPhenomenon
Indicates that an entity experiences or is characterized by a particular phenomenon occurring during the winter season.
- 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_69e7ab333b508190b6d708d8d9a328ed |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fe5f81388190a7352c5782b19d80 |
completed | May 2, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 5:37 a.m.