Triple
T2900090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erg Chigaga |
E62633
|
entity |
| Predicate | extremeSeason |
P17982
|
FINISHED |
| Object | very hot summers |
—
|
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: very hot summers | Statement: [Erg Chigaga, extremeSeason, very hot summers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: extremeSeason Context triple: [Erg Chigaga, extremeSeason, very hot summers]
-
A.
hasExtremeWeatherCharacteristic
chosen
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
B.
coldestSeason
Indicates the season during which a place or region experiences its lowest typical temperatures compared to other seasons.
-
C.
affectedSeason
Indicates that one entity has an influence on, or causes a change in, a particular season.
-
D.
winterCharacteristic
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
E.
summerWinterCycle
Indicates a recurring transition between summer and winter seasons, capturing the cyclical change in conditions or states across these two periods.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe0b081308190af8875151fb11c4e |
completed | March 7, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69abdd19bac881908f047d616aca8438 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:10 p.m.