Triple
T3624726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ullr |
E76808
|
entity |
| Predicate | seasonalAssociation |
P1166
|
FINISHED |
| Object | 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: winter | Statement: [Ullr, seasonalAssociation, winter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seasonalAssociation Context triple: [Ullr, seasonalAssociation, winter]
-
A.
affectedSeason
Indicates that one entity has an influence on, or causes a change in, a particular season.
-
B.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
C.
hasSeasonalEvents
Indicates that an entity organizes or experiences events that occur only during specific seasons or times of the year.
-
D.
season
chosen
Indicates that an entity participates in, is associated with, or occurs during a particular season or seasonal period.
-
E.
associatedWithWeather
Indicates a relationship where something is connected or related to weather conditions or phenomena.
- 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_69ad85dc03948190b35b7189e4175bcc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc2d9845c8190ad65b2471000dfa0 |
completed | March 8, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69adb8410a5881909c94818d7060b2b0 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:23 p.m.