Triple
T9697701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luo people of Tanzania |
E234694
|
entity |
| Predicate | usesLanguageAlongsideEthnicLanguage |
P41297
|
FINISHED |
| Object | Swahili |
—
|
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: Swahili | Statement: [Luo people of Tanzania, usesLanguageAlongsideEthnicLanguage, Swahili]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLanguageAlongsideEthnicLanguage Context triple: [Luo people of Tanzania, usesLanguageAlongsideEthnicLanguage, Swahili]
-
A.
usesLanguageFamily
Indicates that an entity communicates or operates using a language that belongs to a specified language family.
-
B.
ethnicLanguageStatus
Indicates the status or role of a language in relation to a particular ethnic group (e.g., primary, secondary, heritage, or minority language).
-
C.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
D.
usesLanguageSubfamily
Indicates that one entity communicates or operates using a language that belongs to a specified language subfamily.
-
E.
coexistsWithLanguage
chosen
Indicates that one entity exists or functions alongside a particular language at the same time, without excluding or replacing it.
- 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d3c02e0819098d05c68805689f1 |
completed | April 1, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69cd03b641408190942464eaf174c6b5 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:18 p.m.