Triple
T7333893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camden, South Carolina |
E169074
|
entity |
| Predicate | averageJanuaryHighF |
P5274
|
FINISHED |
| Object | 55 |
—
|
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: 55 | Statement: [Camden, South Carolina, averageJanuaryHighF, 55]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageJanuaryHighF Context triple: [Camden, South Carolina, averageJanuaryHighF, 55]
-
A.
averageHighTemperatureInJanuary
chosen
Indicates the typical or mean value of the highest daily temperatures recorded during the month of January for a given location.
-
B.
averageWinterHighF
Indicates the typical or mean high temperature, measured in degrees Fahrenheit, during the winter season for the referenced entity.
-
C.
averageJanuaryLowTemperature
Indicates the typical minimum daily temperature experienced in a location during the month of January.
-
D.
averageWarmestMonth
Indicates the relationship between a place and the month in which its long-term average temperature is highest.
-
E.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
- 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_69c68a568a6481908f11e20db7bc8446 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:04 p.m.