Triple
T24531433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Andes, Chile |
E606820
|
entity |
| Predicate | distanceToMendoza |
P156624
|
FINISHED |
| Object | approximately 300 km west |
—
|
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 300 km west | Statement: [Los Andes, Chile, distanceToMendoza, approximately 300 km west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMendoza Context triple: [Los Andes, Chile, distanceToMendoza, approximately 300 km west]
-
A.
distanceToBahíaBlanca
Indicates the measured distance between a given entity and the location of Bahía Blanca.
-
B.
distanceToNeuquénCity
Indicates the spatial distance between a given location and the city of Neuquén.
-
C.
distanceToNeuquénCity_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Neuquén.
-
D.
distanceFromBuenosAires
Indicates the measured distance between a given entity’s location and the city of Buenos Aires.
-
E.
distanceFromBariloche
Indicates the measured distance between a given entity or location and Bariloche.
- 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_69e2c4c90c848190b23c4303620dcaaf |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:25 a.m.