Triple
T11303072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabye language |
E267643
|
entity |
| Predicate | alternateName |
P39
|
FINISHED |
| Object | Kabye |
E759512
|
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: Kabye | Statement: [Kabye language, alternateName, Kabye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kabye Context triple: [Kabye language, alternateName, Kabye]
-
A.
Kabye
chosen
Kabye is a Gur language spoken primarily in northern Togo and parts of neighboring West African countries by the Kabye people.
-
B.
Duékoué
Duékoué is a town in western Côte d'Ivoire that became notorious as a major site of violence and massacres during the country's civil conflicts.
-
C.
Koné
Koné is a principal town and administrative center on New Caledonia’s main island, Grande Terre.
-
D.
Ziguinchor
Ziguinchor is a major city in southern Senegal, serving as the regional capital of Casamance and an important cultural and economic hub.
-
E.
Tenkodogo, Burkina Faso
Tenkodogo is a historic town in eastern Burkina Faso, considered one of the country’s oldest settlements and an important regional center for the Gurma people.
- 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_69e542df01fc81908539407e20543002 |
completed | April 19, 2026, 9:02 p.m. |
Created at: April 8, 2026, 9:32 p.m.