Triple
T38153979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xalapa region |
E952831
|
entity |
| Predicate | hasFrequentWeather |
P2044
|
FINISHED |
| Object | fog |
—
|
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: fog | Statement: [Xalapa region, hasFrequentWeather, fog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrequentWeather Context triple: [Xalapa region, hasFrequentWeather, fog]
-
A.
hasHighPrecipitation
Indicates that a location or time period experiences a large amount of precipitation, such as rain or snow, relative to a defined standard or average.
-
B.
hasWeather
chosen
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
C.
hasSnowfallFrequency
Indicates how often snowfall occurs for or at a given entity.
-
D.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
E.
typicalPrecipitationPattern
Indicates the usual or characteristic pattern of precipitation associated with a place, time period, or climate condition.
- 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_69f76f0a67f4819080c492f61d688fcc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:21 p.m.