Triple
T2818083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tshiluba |
E54338
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object |
Ciluba
Ciluba is a Bantu language spoken primarily in the Democratic Republic of the Congo, especially in the Kasai region.
|
E308987
|
NE FINISHED |
How this triple was built (4 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: Ciluba | Statement: [Tshiluba, alternativeName, Ciluba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ciluba Context triple: [Tshiluba, alternativeName, Ciluba]
-
A.
Combarbalá
Combarbalá is a small Chilean town and municipality in the Coquimbo Region, known for its semi-arid landscapes, goat farming, and distinctive combarbalite stone crafts.
-
B.
Itabaiana
Itabaiana is a prominent inland city in the Brazilian state of Sergipe, known for its vibrant commerce, agricultural production, and strategic location as a regional hub.
-
C.
Corumbá
Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
-
D.
Canindé
Canindé is a municipality in the Brazilian state of Ceará known for its major religious pilgrimages honoring Saint Francis of Assisi.
-
E.
Caxangá
Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ciluba Triple: [Tshiluba, alternativeName, Ciluba]
Generated description
Ciluba is a Bantu language spoken primarily in the Democratic Republic of the Congo, especially in the Kasai region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ciluba Target entity description: Ciluba is a Bantu language spoken primarily in the Democratic Republic of the Congo, especially in the Kasai region.
-
A.
Combarbalá
Combarbalá is a small Chilean town and municipality in the Coquimbo Region, known for its semi-arid landscapes, goat farming, and distinctive combarbalite stone crafts.
-
B.
Itabaiana
Itabaiana is a prominent inland city in the Brazilian state of Sergipe, known for its vibrant commerce, agricultural production, and strategic location as a regional hub.
-
C.
Corumbá
Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
-
D.
Canindé
Canindé is a municipality in the Brazilian state of Ceará known for its major religious pilgrimages honoring Saint Francis of Assisi.
-
E.
Caxangá
Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
- F. None of above. chosen
Provenance (5 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde6c44d881909f8275b6466e2f20 |
completed | March 7, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b055d3dbb8819094df5e6751dd96c4 |
completed | March 10, 2026, 5:33 p.m. |
| NEDg | Description generation | batch_69b05dc976848190933a988263ef1e40 |
completed | March 10, 2026, 6:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b061a2b8b48190ba01866a11a0b0c5 |
completed | March 10, 2026, 6:23 p.m. |
Created at: March 6, 2026, 9:59 p.m.