Triple
T430185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Democratic Republic of the Congo |
E9695
|
entity |
| Predicate | recognizedNationalLanguage |
P236
|
FINISHED |
| Object |
Tshiluba
Tshiluba is a Bantu language widely spoken in south-central Democratic Republic of the Congo, particularly in the Kasai region.
|
E54338
|
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: Tshiluba | Statement: [Democratic Republic of the Congo, recognizedNationalLanguage, Tshiluba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tshiluba Context triple: [Democratic Republic of the Congo, recognizedNationalLanguage, Tshiluba]
-
A.
Kibondo
Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
-
B.
Lozi
Lozi is a Bantu language spoken primarily by the Lozi people in western Zambia and surrounding regions of southern Africa.
-
C.
Kigoma
Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
-
D.
Wanetsi
Wanetsi is a distinct and archaic variety of Pashto spoken by a small community in parts of Afghanistan and Pakistan.
-
E.
Jacob Mudenda
Jacob Mudenda is a Zimbabwean politician and lawyer who serves as the Speaker of the National Assembly and is a prominent member of the ruling ZANU–PF party.
- 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: Tshiluba Triple: [Democratic Republic of the Congo, recognizedNationalLanguage, Tshiluba]
Generated description
Tshiluba is a Bantu language widely spoken in south-central Democratic Republic of the Congo, particularly in the Kasai region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tshiluba Target entity description: Tshiluba is a Bantu language widely spoken in south-central Democratic Republic of the Congo, particularly in the Kasai region.
-
A.
Kibondo
Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
-
B.
Lozi
Lozi is a Bantu language spoken primarily by the Lozi people in western Zambia and surrounding regions of southern Africa.
-
C.
Kigoma
Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
-
D.
Wanetsi
Wanetsi is a distinct and archaic variety of Pashto spoken by a small community in parts of Afghanistan and Pakistan.
-
E.
Jacob Mudenda
Jacob Mudenda is a Zimbabwean politician and lawyer who serves as the Speaker of the National Assembly and is a prominent member of the ruling ZANU–PF party.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eeedf68c81908473d6c6600961bd |
completed | Feb. 28, 2026, 1:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a42f6938a08190a6c1433242832dea |
completed | March 1, 2026, 12:22 p.m. |
| NEDg | Description generation | batch_69a43038d2348190a348e6661d27dde4 |
completed | March 1, 2026, 12:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a430f6c6f88190b5aecfe3c4c8957d |
completed | March 1, 2026, 12:28 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.