Triple
T18137263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subantarctic Mode Water |
E434168
|
entity |
| Predicate | formedSeason |
P130595
|
FINISHED |
| Object | austral winter |
—
|
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: austral winter | Statement: [Subantarctic Mode Water, formedSeason, austral winter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formedSeason Context triple: [Subantarctic Mode Water, formedSeason, austral winter]
-
A.
wonSeasonOf
Indicates that one entity emerged as the overall winner of a particular season of a competition, show, or series involving the other entity.
-
B.
originalSeasonStart
Indicates the date or point in time when a season (such as a sports league or TV series) first began or was originally launched.
-
C.
seasonAfter
Indicates that one season occurs chronologically immediately after another season in a sequence.
-
D.
hasSeason
Indicates that an entity possesses, occurs during, or is associated with a particular season or set of seasons.
-
E.
affectedSeason
Indicates that one entity has an influence on, or causes a change in, a particular 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de089f1881908dff9835be5129a1 |
completed | April 19, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69e43317d11c81908d1dc14921566b47 |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:29 a.m.