Triple
T8219732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fog City |
E192026
|
entity |
| Predicate | notableSeasonality |
P955
|
FINISHED |
| Object | foggiest in autumn and 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: foggiest in autumn and winter | Statement: [Fog City, notableSeasonality, foggiest in autumn and winter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableSeasonality Context triple: [Fog City, notableSeasonality, foggiest in autumn and winter]
-
A.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
B.
hasSeasonalPattern
chosen
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
C.
notableSeason
Indicates that a particular season is especially significant or noteworthy in relation to an entity (such as a person, team, or series).
-
D.
affectedSeason
Indicates that one entity has an influence on, or causes a change in, a particular season.
-
E.
hasSeasonalHighlight
Indicates that something features a notable or emphasized aspect during a particular season or time of year.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb7772b76c8190b1952650c736eb91 |
completed | March 31, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69cb36af41e081909dee92b9bc4947f1 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:45 p.m.