Triple
T35670379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sicuani |
E1030697
|
entity |
| Predicate | approximateDistanceToCusco |
P14767
|
FINISHED |
| Object | about 140 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 140 kilometres | Statement: [Sicuani, approximateDistanceToCusco, about 140 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateDistanceToCusco Context triple: [Sicuani, approximateDistanceToCusco, about 140 kilometres]
-
A.
distanceFromCusco
chosen
Indicates the measured spatial distance between a given location or entity and the city of Cusco.
-
B.
distanceFromLaPazApproximate
Indicates an approximate measure of how far something is from La Paz, typically expressed as a rough distance rather than an exact value.
-
C.
distanceFromArequipa
Indicates the spatial distance between a given location and the city of Arequipa.
-
D.
distanceFromPotosiApproximate
Indicates an approximate measure of how far something is from Potosi.
-
E.
distanceFromLima
Indicates the measured distance between a given place or object and the city of Lima.
- 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_69f76e0acfc0819082c8495c2210ce73 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff6c061c6c81909ff485e9cafc88a2 |
completed | May 9, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69ff6aaf886c8190a3c87d089453f3de |
completed | May 9, 2026, 5:11 p.m. |
Created at: May 3, 2026, 4:05 p.m.