Triple
T28362269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aconcagua River basin |
E718394
|
entity |
| Predicate | mainRiverLength_km |
P59548
|
FINISHED |
| Object | approximately 142 |
—
|
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 142 | Statement: [Aconcagua River basin, mainRiverLength_km, approximately 142]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainRiverLength_km Context triple: [Aconcagua River basin, mainRiverLength_km, approximately 142]
-
A.
riverLength
Indicates the measured extent of a river from its source to its mouth, typically expressed as a linear distance.
-
B.
waterwayLengthKilometres
chosen
Indicates the total length of a waterway, measured in kilometres.
-
C.
riverLengthContext
Indicates the contextual or situational information under which a river’s length is measured or considered.
-
D.
hasLongestRiver
Indicates that one entity possesses or contains the river that is longer than any other river associated with the compared entities.
-
E.
largestInflowRiver
Indicates that one river has the greatest volume of water flowing into a specified body (such as a lake, sea, or another river) compared to all other contributing rivers.
- 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_69eff6ed5af48190be4e0adf298223e0 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 12:52 a.m.