Triple
T38510396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gulmancema |
E921886
|
entity |
| Predicate | hasSpeakersInRuralAreasOf |
P8344
|
FINISHED |
| Object | Burkina Faso |
—
|
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: Burkina Faso | Statement: [Gulmancema, hasSpeakersInRuralAreasOf, Burkina Faso]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeakersInRuralAreasOf Context triple: [Gulmancema, hasSpeakersInRuralAreasOf, Burkina Faso]
-
A.
spokenInRuralAreasOf
chosen
Indicates that something (typically a language, dialect, or speech variety) is used or spoken primarily in the rural areas of a specified region or country.
-
B.
hasSpeakersIn
Indicates that an entity (such as an event, conference, or session) includes or is associated with speakers located in or belonging to a specified place or group.
-
C.
hasSpeakersAlong
Indicates that something is equipped with or accompanied by speakers positioned along its length or path.
-
D.
haveSpeakersWhoAre
Indicates that an entity has speakers characterized by a specified property, status, or attribute.
-
E.
hasRuralDistricts
Indicates that an entity is associated with, contains, or is administratively linked to one or more rural districts.
- 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_69f76ea3c5448190aa7002fc1ba3f874 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff246e0d4481908bcec718e1d4025b |
completed | May 9, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69ff23cb70ac81909b776ace4597ae9c |
completed | May 9, 2026, 12:08 p.m. |
Created at: May 3, 2026, 4:32 p.m.