Triple
T26848202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Norma |
E675981
|
entity |
| Predicate | hasWinterSeason |
P164481
|
FINISHED |
| Object | approximately December to April |
—
|
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: approximately December to April | Statement: [La Norma, hasWinterSeason, approximately December to April]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWinterSeason Context triple: [La Norma, hasWinterSeason, approximately December to April]
-
A.
hasWinterPhenomenon
Indicates that an entity experiences or is characterized by a particular phenomenon occurring during the winter season.
-
B.
hasLongWinterSeason
Indicates that the referenced entity experiences a winter season that lasts for an extended or unusually long period of time.
-
C.
hasWinterActivitySeason
Indicates that an entity’s primary period for engaging in a particular activity occurs during the winter season.
-
D.
hasFrozenInWinter
Indicates that something becomes or has become frozen during the winter season.
-
E.
hasWinterRoute
Indicates that an entity has an associated route or path specifically designated for use during the winter season.
- 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_69eee9b8d5e88190a07d3455c0fbb21f |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f64e6e8c9081908ce4d364aa26147a |
completed | May 2, 2026, 7:20 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
| PDg | Predicate description generation | batch_69f64db8ee1881909362701d72ffe282 |
completed | May 2, 2026, 7:17 p.m. |
Created at: April 27, 2026, 5:14 a.m.