Triple
T11303069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabye language |
E267643
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | Kabɩyɛ |
E209614
|
NE 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: Kabɩyɛ | Statement: [Kabye language, nativeName, Kabɩyɛ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kabɩyɛ Context triple: [Kabye language, nativeName, Kabɩyɛ]
-
A.
Kabiye
chosen
Kabiye is a Gur language spoken primarily in northern Togo and recognized as one of the country's major national languages.
-
B.
Kumba
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
-
C.
Kumba
Kumba is a major town in southwestern Cameroon known as a commercial hub and cultural crossroads where languages like Cameroonian Pidgin English are widely used.
-
D.
Chakwali
Chakwali is a regional dialect of Potohari Punjabi spoken in and around the Chakwal area of Pakistan’s Punjab province.
-
E.
Kilembe
Kilembe is a town in western Uganda that serves as a common starting point for treks to the Rwenzori Mountains, including ascents of Margherita Peak.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a5c3788190ba54eda514b97903 |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a57366081908a05fc52c5d4074c |
completed | April 19, 2026, 5:01 p.m. |
Created at: April 8, 2026, 9:32 p.m.