Triple
T23644359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazil–Paraguay border |
E583988
|
entity |
| Predicate | adjacentToParaguayanDepartment |
P153013
|
FINISHED |
| Object | Alto Paraná Department |
—
|
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: Alto Paraná Department | Statement: [Brazil–Paraguay border, adjacentToParaguayanDepartment, Alto Paraná Department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentToParaguayanDepartment Context triple: [Brazil–Paraguay border, adjacentToParaguayanDepartment, Alto Paraná Department]
-
A.
regionInBolivia
Indicates that a specified region is geographically located within the country of Bolivia.
-
B.
regionOnPeruSide
Indicates that a region is located on the side of a boundary or border that belongs to or is associated with Peru.
-
C.
isPartOfChileanTerritory
Indicates that one entity is geographically or politically included within the official territory of Chile.
-
D.
nearCityInUruguay
Indicates that one entity is located close to, or in the vicinity of, a specified city within Uruguay.
-
E.
borderingRepublic
Indicates that one republic shares a land or maritime border with another republic.
- 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_69e248fefafc81909656921192f30e80 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b2832d9c8190b19c55deee39eff2 |
completed | April 29, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f1233300bc8190ac1639bdca1d7d99 |
completed | April 28, 2026, 9:14 p.m. |
Created at: April 17, 2026, 6:48 p.m.