Triple
T7852726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cathedral City |
E182094
|
entity |
| Predicate | regionClimateDescription |
P51674
|
FINISHED |
| Object | hot summers and mild winters |
—
|
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: hot summers and mild winters | Statement: [Cathedral City, regionClimateDescription, hot summers and mild winters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionClimateDescription Context triple: [Cathedral City, regionClimateDescription, hot summers and mild winters]
-
A.
averageClimateDescription
chosen
Indicates the general or typical climate characteristics associated with an entity, often summarizing conditions like temperature and precipitation over time.
-
B.
climatologicalType
Indicates the classification of a climate or weather pattern that characterizes a place, period, or condition.
-
C.
climatologicalRegion
Indicates that one entity is a climatological region associated with, or characterizing the climate of, another entity.
-
D.
shareClimateZones
Indicates that two entities are located in regions classified under the same climate zone or zones.
-
E.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18ed56d481909266d862e0ae152d |
completed | March 31, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:51 p.m.