Triple
T12653960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loko |
E302234
|
entity |
| Predicate | regionallyImportantLanguageIn |
P10892
|
FINISHED |
| Object | north-central Sierra Leone |
—
|
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: north-central Sierra Leone | Statement: [Loko, regionallyImportantLanguageIn, north-central Sierra Leone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionallyImportantLanguageIn Context triple: [Loko, regionallyImportantLanguageIn, north-central Sierra Leone]
-
A.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
-
B.
regionLanguage
chosen
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
C.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
D.
majorityLanguageOf
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
E.
recognizedRegionalLanguage
Indicates that a language holds officially recognized status within a specific region or subnational jurisdiction.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b78ce8819091f15dd5013e6da5 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:18 p.m.