Triple
T1618011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Río de la Plata |
E34763
|
entity |
| Predicate | widthAtMouth |
P619
|
FINISHED |
| Object | about 220 km |
—
|
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: about 220 km | Statement: [Río de la Plata, widthAtMouth, about 220 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: widthAtMouth Context triple: [Río de la Plata, widthAtMouth, about 220 km]
-
A.
mouthNear
Indicates that one entity’s mouth is positioned close to another entity or object in space.
-
B.
mouth
Indicates that one entity is the mouth (oral opening) of another entity, typically serving as the location for ingestion, speech, or related functions.
-
C.
mouthOf
Indicates the location where one entity (typically a river or similar feature) empties into or opens out into another, larger body or feature.
-
D.
width
chosen
Indicates the measurement of how wide an entity is, typically the extent of its horizontal dimension from side to side.
-
E.
isNarrowestPartOf
Indicates that one entity constitutes the slimmest or most constricted section within the extent or structure of another entity.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fef600c819080fe75c42c8e6dac |
completed | March 5, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69a907c52a548190b648a31ea306dd5b |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.