Triple
T30980337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perezida wa Repubulika y’u Rwanda |
E789353
|
entity |
| Predicate | hasTitleInSwahili |
P116291
|
FINISHED |
| Object | Rais wa Jamhuri ya Rwanda |
—
|
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: Rais wa Jamhuri ya Rwanda | Statement: [Perezida wa Repubulika y’u Rwanda, hasTitleInSwahili, Rais wa Jamhuri ya Rwanda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleInSwahili Context triple: [Perezida wa Repubulika y’u Rwanda, hasTitleInSwahili, Rais wa Jamhuri ya Rwanda]
-
A.
hasTitleInAfrikaans
Indicates that an entity has a specific title expressed in the Afrikaans language.
-
B.
SwahiliName
chosen
Indicates that one entity is the Swahili-language name or designation for the other entity.
-
C.
hasTitleInEsperanto
Indicates that an entity has a specific title expressed in the Esperanto language.
-
D.
hasTitleInLanguage
Indicates that an entity has a specific title expressed in a particular language.
-
E.
hasTitleIn
Indicates that an entity holds or is associated with a specific title within a particular context, domain, or language.
- 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_69f224c4831c8190be53924ec25a150a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fbaebc8f2c8190b94f1b4a3ec92e8c |
completed | May 6, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
Created at: April 29, 2026, 8:55 p.m.