Triple
T24240194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loncopué |
E603199
|
entity |
| Predicate | distanceToProvincialCapital |
P117649
|
FINISHED |
| Object | located west of Neuquén city |
—
|
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: located west of Neuquén city | Statement: [Loncopué, distanceToProvincialCapital, located west of Neuquén city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToProvincialCapital Context triple: [Loncopué, distanceToProvincialCapital, located west of Neuquén city]
-
A.
distanceToProvinceCapital_km
chosen
Indicates the distance, measured in kilometers, between a given location and the capital city of its province.
-
B.
distanceFromRegionalCapital
Indicates the measured spatial distance between a given place and its corresponding regional capital.
-
C.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
D.
distanceToDepartmentCapital
Indicates the measured distance between a given location and the capital city of its corresponding department.
-
E.
prefecturalCapitalDistanceRelation
Indicates a spatial relationship specifying the distance between an entity and the capital city of its prefecture.
- 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_69e2953f631c819097cbb421046bd417 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28a9f812c81909dba8fbb54d8985c |
completed | April 29, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:03 a.m.