Triple
T29714397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itapúa Department |
E751867
|
entity |
| Predicate | crossBorderCity |
P15361
|
FINISHED |
| Object | Posadas |
—
|
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: Posadas | Statement: [Itapúa Department, crossBorderCity, Posadas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossBorderCity Context triple: [Itapúa Department, crossBorderCity, Posadas]
-
A.
crossBorderRegion
Indicates a region that spans or intersects the boundary between two or more distinct territorial or jurisdictional areas.
-
B.
shareMajorBorderCities
Indicates that two regions or countries have a shared border along which there are one or more major cities situated on or near that boundary.
-
C.
borderTownAcrossBorder
Indicates that a town lies on one side of a border directly opposite or adjacent to a town on the other side of that border.
-
D.
hasBorderCity
chosen
Indicates that one location is a city situated on or very near the border of another geographic or political region.
-
E.
oppositeTownAcrossBorder
Indicates that one town is located directly across a border from another town, positioned as its opposite counterpart.
- 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_69f0d62748848190b030d0a703629a7d |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 28, 2026, 7:33 p.m.