Triple
T76460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bogotá |
E1526
|
entity |
| Predicate | averageTemperature |
P4814
|
FINISHED |
| Object | about 14 °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: about 14 °C | Statement: [Bogotá, averageTemperature, about 14 °C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageTemperature Context triple: [Bogotá, averageTemperature, about 14 °C]
-
A.
hasAverageSpringTemperature
Indicates that an entity is associated with a specific average temperature value measured over the spring season.
-
B.
averageAnnualPrecipitation
Indicates the typical total amount of precipitation an entity receives over the course of a year, averaged across multiple years.
-
C.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
D.
weatherCondition
Indicates the type of atmospheric state or weather pattern (e.g., sunny, rainy, snowy) affecting a location or time period.
-
E.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
- F. None of above. chosen
Provenance (4 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2559892dc81909303f2eefdc0025f |
completed | Feb. 28, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69a24eaf99e481908e8d314577e22ecf |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a25597b6c48190849c3e9e6351b983 |
completed | Feb. 28, 2026, 2:40 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.