Triple
T1260086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iguazu Falls |
E12477
|
entity |
| Predicate | totalWidth |
P3989
|
FINISHED |
| Object | about 2.7 kilometres |
—
|
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 2.7 kilometres | Statement: [Iguazu Falls, totalWidth, about 2.7 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalWidth Context triple: [Iguazu Falls, totalWidth, about 2.7 kilometres]
-
A.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
B.
totalHeight
Indicates the combined vertical measurement resulting from adding the heights of one or more entities.
-
C.
hasWidth
chosen
Indicates that an entity possesses a specific measurement or extent along its width dimension.
-
D.
hasApproximateMaximumWidth
Indicates that an entity’s maximum width is known only approximately, rather than as an exact value.
-
E.
minimumWidth
Indicates that there is a specified smallest allowable or required width for something in the relationship.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc503e88190b237210a61228dd8 |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6eefbc81908dddd7d2ef368186 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:50 p.m.