Triple
T6331232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lerma River basin |
E142384
|
entity |
| Predicate | receivesPrecipitationFrom |
P15750
|
FINISHED |
| Object | summer monsoon rains |
—
|
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 monsoon rains | Statement: [Lerma River basin, receivesPrecipitationFrom, summer monsoon rains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receivesPrecipitationFrom Context triple: [Lerma River basin, receivesPrecipitationFrom, summer monsoon rains]
-
A.
receivesMoistureFrom
chosen
Indicates that one entity obtains or is supplied with moisture (such as water, humidity, or precipitation) from another entity.
-
B.
associatedWithPrecipitationType
Indicates that there is a relationship between an entity and a specific type or category of precipitation (such as rain, snow, or hail).
-
C.
receivesFreshwaterFrom
Indicates that one entity is supplied with or obtains freshwater from another entity as its source.
-
D.
primaryRainfallSource
Indicates that one entity is the main origin or contributing source of rainfall for another entity or region.
-
E.
averageAnnualPrecipitation
Indicates the typical total amount of precipitation an entity receives 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_69c008d4d8e88190ad301c05b08722ac |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06514cbe8819096dbeb17ccb3e3d5 |
completed | March 22, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69c060e7e2d48190af9d004236466788 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:30 p.m.