Triple
T559637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altiplano plateau |
E13418
|
entity |
| Predicate | precipitationPattern |
P955
|
FINISHED |
| Object | summer rainfall |
—
|
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: summer rainfall | Statement: [Altiplano plateau, precipitationPattern, summer rainfall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: precipitationPattern Context triple: [Altiplano plateau, precipitationPattern, summer rainfall]
-
A.
averageAnnualPrecipitation
Indicates the typical total amount of precipitation an entity receives over the course of a year, averaged across multiple years.
-
B.
hasSeasonalPattern
chosen
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
C.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
D.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
E.
averageAnnualSnowfall
Indicates the typical amount of snow that falls in a given location over the course of a year, averaged across multiple years.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499e13694819087a236bffa6601a9 |
completed | March 1, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69a494befb8481908bb4e2e9f31e343b |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.