Triple
T7851207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Plata, Maryland |
E182056
|
entity |
| Predicate | averageWinterLowTemperatureF |
P17371
|
FINISHED |
| Object | around 27 |
—
|
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: around 27 | Statement: [La Plata, Maryland, averageWinterLowTemperatureF, around 27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageWinterLowTemperatureF Context triple: [La Plata, Maryland, averageWinterLowTemperatureF, around 27]
-
A.
averageWinterLowTemperature
chosen
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
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.
averageColdestMonth
Indicates the month in which an entity experiences the lowest average temperature over a given period.
-
E.
averageMinTemperatureColdestMonth
Indicates the lowest average minimum temperature recorded during the coldest month in a given location or period.
- 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_69cb18eaac508190bf373b1d50b52e1e |
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, 4:50 p.m.