Triple
T6734836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narsinghpur |
E153726
|
entity |
| Predicate | summerTemperatureRangeApprox |
P71961
|
FINISHED |
| Object | up to about 45 °C |
—
|
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: up to about 45 °C | Statement: [Narsinghpur, summerTemperatureRangeApprox, up to about 45 °C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: summerTemperatureRangeApprox Context triple: [Narsinghpur, summerTemperatureRangeApprox, up to about 45 °C]
-
A.
summerTemperatureRange_C
chosen
Indicates the range of temperatures, measured in degrees Celsius, that typically occur during the summer period for a given entity or location.
-
B.
summerClimate
Indicates the typical weather conditions or characteristics that prevail in a place during the summer season.
-
C.
summerHighTemperaturesOftenExceed
Indicates that during the summer season, the high temperatures in a given location frequently surpass a specified threshold.
-
D.
averageSummerTemperatureC
Indicates the typical or mean air temperature, measured in degrees Celsius, experienced at a location during the summer season.
-
E.
summerBase
Indicates a base or location where an entity is situated or operates specifically during the summer season.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d16ecbe08190b019d547f631a725 |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d09067a0819087ed6c820f4699f8 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:09 p.m.