Triple
T1211667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roanoke, Texas |
E26012
|
entity |
| Predicate | averageSummerHighTemperatureC |
P19593
|
FINISHED |
| Object | about 36 |
—
|
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: about 36 | Statement: [Roanoke, Texas, averageSummerHighTemperatureC, about 36]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageSummerHighTemperatureC Context triple: [Roanoke, Texas, averageSummerHighTemperatureC, about 36]
-
A.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
B.
averageMaxTemperatureWarmestMonth
Indicates the highest average temperature recorded in the warmest month of a given time period or location.
-
C.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
D.
averageHighTemperatureInJuly
Indicates the typical or mean value of the highest daily temperatures recorded during the month of July for a given location.
-
E.
summerHighTemperaturesOftenExceed
chosen
Indicates that during the summer season, the high temperatures in a given location frequently surpass a specified threshold.
- 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_69a4948331fc8190b531ac9bec71c491 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bde581308190bbe30683bf6c48c3 |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb62a7c08190a79dcb6ff72ac99b |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.