Triple
T23935416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Libertadores Pass |
E602621
|
entity |
| Predicate | nearBorderTownOnArgentineSide |
P80236
|
FINISHED |
| Object | Uspallata |
—
|
NE NERFINISHED |
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: Uspallata | Statement: [Los Libertadores Pass, nearBorderTownOnArgentineSide, Uspallata]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearBorderTownOnArgentineSide Context triple: [Los Libertadores Pass, nearBorderTownOnArgentineSide, Uspallata]
-
A.
nearCityInArgentina
chosen
Indicates that one entity is located close to, but not necessarily within, a specified city in Argentina.
-
B.
adjacentToParaguayanDepartment
Indicates that one entity is directly next to or shares a boundary with a department located in Paraguay.
-
C.
distanceToBahíaBlanca
Indicates the measured distance between a given entity and the location of Bahía Blanca.
-
D.
widthNearBuenosAires
Indicates that an entity’s width measurement is geographically close to, or approximately aligned with, the width at the location of Buenos Aires.
-
E.
distanceFromBuenosAires
Indicates the measured distance between a given entity’s location and the city of Buenos Aires.
- 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_69e2953cf6e081909b8e25a10a52dddc |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1cf9e8abc8190a3028a358265912e |
completed | April 29, 2026, 9:30 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:02 p.m.