Triple
T15228692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noveleta |
E363941
|
entity |
| Predicate | hasClimateSeason |
P103107
|
FINISHED |
| Object | wet 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: wet season | Statement: [Noveleta, hasClimateSeason, wet season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClimateSeason Context triple: [Noveleta, hasClimateSeason, wet season]
-
A.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
B.
averageClimateSeason
chosen
Indicates the typical or prevailing climate conditions associated with a particular season in a given location.
-
C.
hasClimateContext
Indicates that something is associated with, influenced by, or relevant to climate-related conditions, factors, or considerations.
-
D.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
E.
hasDrySeasonCause
Indicates that one factor or condition is the underlying cause of a location or region experiencing a dry 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078ccdf48190b34eabd9e24e45a1 |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:12 a.m.