Triple
T4888850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denton, Texas |
E109507
|
entity |
| Predicate | averageHighTemperatureJulyC |
P5273
|
FINISHED |
| Object | 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: 36 | Statement: [Denton, Texas, averageHighTemperatureJulyC, 36]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageHighTemperatureJulyC Context triple: [Denton, Texas, averageHighTemperatureJulyC, 36]
-
A.
averageHighTemperatureInJuly
chosen
Indicates the typical or mean value of the highest daily temperatures recorded during the month of July for a given location.
-
B.
averageWarmestMonth
Indicates the relationship between a place and the month in which its long-term average temperature is highest.
-
C.
averageMaxTemperatureWarmestMonth
Indicates the highest average temperature recorded in the warmest month of a given time period or location.
-
D.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
E.
averageHighTemperatureInJanuary
Indicates the typical or mean value of the highest daily temperatures recorded during the month of January for a given location.
- 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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.