Triple
T5573845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Calafate |
E146267
|
entity |
| Predicate | distanceToPeritoMorenoGlacier |
P64523
|
FINISHED |
| Object | approximately 80 kilometers |
—
|
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 80 kilometers | Statement: [El Calafate, distanceToPeritoMorenoGlacier, approximately 80 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPeritoMorenoGlacier Context triple: [El Calafate, distanceToPeritoMorenoGlacier, approximately 80 kilometers]
-
A.
distanceFromLaPazApproximate
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.
distanceFromBuenosAires
Indicates the measured distance between a given entity’s location and the city of Buenos Aires.
-
D.
distanceToLaPlata
Indicates the measured or calculated distance between a given entity and the location La Plata.
-
E.
distanceFromCusco
Indicates the measured spatial distance between a given location or entity and the city of Cusco.
- F. None of above. chosen
Provenance (4 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02052dd0481909aba6863831357eb |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b147cc081909237f3f2967d4cb8 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0684908190ae2d14f0bd2ab892 |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:37 p.m.