Triple
T8710148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rahanweyn |
E206753
|
entity |
| Predicate | languageRole |
P84672
|
FINISHED |
| Object | regional lingua franca in parts of southern Somalia |
—
|
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: regional lingua franca in parts of southern Somalia | Statement: [Rahanweyn, languageRole, regional lingua franca in parts of southern Somalia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageRole Context triple: [Rahanweyn, languageRole, regional lingua franca in parts of southern Somalia]
-
A.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
B.
EnglishRole
Indicates that one entity serves a particular role or function within the context of the English language for another entity.
-
C.
languageStandardizationRole
Indicates the role an entity plays in establishing, maintaining, or influencing the standardization of a language.
-
D.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
-
E.
languageLabel
Indicates the human-readable name or label of a language associated with an entity or resource.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5c3034708190b895eaf890d62198 |
completed | March 31, 2026, 11:43 p.m. |
| PD | Predicate disambiguation | batch_69cc456bda508190a9aa0fb92760739e |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc582412f48190ae819965bfb0e75d |
completed | March 31, 2026, 11:26 p.m. |
Created at: March 30, 2026, 6:35 p.m.