Triple
T12394089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viacha |
E296071
|
entity |
| Predicate | distanceToLaPaz_km |
P29988
|
FINISHED |
| Object | approximately 22 |
—
|
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 22 | Statement: [Viacha, distanceToLaPaz_km, approximately 22]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLaPaz_km Context triple: [Viacha, distanceToLaPaz_km, approximately 22]
-
A.
distanceFromLaPazApproximate
chosen
Indicates an approximate measure of how far something is from La Paz, typically expressed as a rough distance rather than an exact value.
-
B.
distanceFromPotosiApproximate
Indicates an approximate measure of how far something is from Potosi.
-
C.
distanceFromLima
Indicates the measured distance between a given place or object and the city of Lima.
-
D.
distanceToSantiago_km
Indicates the physical distance, measured in kilometers, between a given location and Santiago.
-
E.
distanceFromCusco
Indicates the measured spatial distance between a given location or entity and the city of Cusco.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fd228488190b216abd1c341563c |
completed | April 10, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69d93ed256788190b704cad171a4824e |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.