Triple
T1126513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maipo River |
E24731
|
entity |
| Predicate | hasWatershedArea |
P1641
|
FINISHED |
| Object | approximately 15,000 square kilometers |
—
|
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: approximately 15,000 square kilometers | Statement: [Maipo River, hasWatershedArea, approximately 15,000 square kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWatershedArea Context triple: [Maipo River, hasWatershedArea, approximately 15,000 square kilometers]
-
A.
hasWatershed
Indicates that one geographic area or feature is part of, drains into, or is hydrologically defined by a particular watershed.
-
B.
watershedArea
Indicates the total land area from which surface water drains into a particular water body or point in the drainage system.
-
C.
hasAreaWaterBody
Indicates that an entity includes, contains, or is associated with a body of water within its area or boundaries.
-
D.
drainageBasinArea
chosen
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
E.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4749ac8190b0fbddac2e9b2586 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.