Triple
T23521709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ñeembucú Department |
E574524
|
entity |
| Predicate | borderWithRiver |
P31306
|
FINISHED |
| Object | Paraguay River |
—
|
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: Paraguay River | Statement: [Ñeembucú Department, borderWithRiver, Paraguay River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderWithRiver Context triple: [Ñeembucú Department, borderWithRiver, Paraguay River]
-
A.
borderedByCountryAcrossRiver
Indicates that one country shares a border with another country, with the boundary specifically formed or separated by a river.
-
B.
bordersAcrossRiver
Indicates that two regions or entities share a boundary with each other that is separated or defined by a river.
-
C.
isOnBorderRiver
Indicates that something is located along or directly adjacent to a river that forms a border between areas.
-
D.
borderRiverContext
Indicates that a river serves as or is involved in forming the boundary between two geographic or political regions within a specific contextual setting.
-
E.
riverFormsBorderWith
chosen
Indicates that a river serves as a boundary line between two geographic or political entities.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa873ad48190a86807bd4f26df82 |
completed | April 29, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:08 p.m.