Triple
T23925460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koyra Chiini |
E602338
|
entity |
| Predicate | spokenInArea |
P67236
|
FINISHED |
| Object | around Timbuktu |
—
|
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: around Timbuktu | Statement: [Koyra Chiini, spokenInArea, around Timbuktu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenInArea Context triple: [Koyra Chiini, spokenInArea, around Timbuktu]
-
A.
spokenInLocality
Indicates that a language, dialect, or speech form is used or spoken within a specific locality or geographic area.
-
B.
spokenInUrbanArea
Indicates that an utterance or speech event occurs within a city or densely populated urban environment.
-
C.
isSpokenAround
chosen
Indicates that something (such as a language, phrase, or expression) is commonly spoken in the vicinity of, or within the general area surrounding, a particular place or entity.
-
D.
spokenInCounty
Indicates that a particular language or dialect is spoken within the geographic area of a specified county.
-
E.
spokenNear
Indicates that one entity spoke in close physical proximity to another entity or location.
- 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_69e2953b928c819095395fa87baca583 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cf1ce7f88190a4afd091b4384558 |
completed | April 29, 2026, 9:27 a.m. |
| PD | Predicate disambiguation | batch_69f16151ebdc819086e9e1d7cc1f4f3c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:44 p.m.