Triple
T31889911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poteet, Texas, United States |
E814118
|
entity |
| Predicate | averageWinterLowTemperatureInF |
P17371
|
FINISHED |
| Object | upper-30s to low-40s |
—
|
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: upper-30s to low-40s | Statement: [Poteet, Texas, United States, averageWinterLowTemperatureInF, upper-30s to low-40s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageWinterLowTemperatureInF Context triple: [Poteet, Texas, United States, averageWinterLowTemperatureInF, upper-30s to low-40s]
-
A.
averageWinterLowTemperature
chosen
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
B.
minimumWinterTemperature
Indicates the lowest temperature typically experienced during the winter season for the subject entity.
-
C.
averageWinterHighF
Indicates the typical or mean high temperature, measured in degrees Fahrenheit, during the winter season for the referenced entity.
-
D.
averageAnnualLowTemperature
Indicates the typical lowest temperature value recorded per year for a given place or period, averaged over multiple years.
-
E.
averageJanuaryLowTemperature
Indicates the typical minimum daily temperature experienced in a location during the month of January.
- 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_69f348ef817481908440e2250319bcc8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b21e7e088190832a3db585daea1c |
completed | May 3, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 30, 2026, 11:57 p.m.