Triple
T19856314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruhuhu River |
E477140
|
entity |
| Predicate | countryBorderRelation |
P137589
|
FINISHED |
| Object | entirely within Tanzania |
—
|
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: entirely within Tanzania | Statement: [Ruhuhu River, countryBorderRelation, entirely within Tanzania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryBorderRelation Context triple: [Ruhuhu River, countryBorderRelation, entirely within Tanzania]
-
A.
countryBordering
Indicates that one country shares a land or maritime boundary directly with another country.
-
B.
sharesInternationalBorderWith
Indicates that two geographic or political entities have a common boundary that is recognized as an international border.
-
C.
countryBorderFormsPartOf
Indicates that a specific border segment is part of the overall boundary between two countries.
-
D.
countryBorderType
Indicates the type or nature of the border relationship that exists between two countries.
-
E.
provinceBordering
Indicates that two provinces share a common boundary or border with each other.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6586c14fc81908d34785f1088b0a9 |
completed | April 20, 2026, 4:46 p.m. |
| PD | Predicate disambiguation | batch_69e537e21d2881909b1be82f02b99d40 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:51 p.m.