Triple
T11093736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bongo language |
E262319
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object |
Dor Bongo
Dor Bongo is an alternative name for the Bongo language, a Central Sudanic language spoken primarily in South Sudan.
|
E905405
|
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: Dor Bongo | Statement: [Bongo language, hasAlternativeName, Dor Bongo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dor Bongo Context triple: [Bongo language, hasAlternativeName, Dor Bongo]
-
A.
Bongo
Bongo is an animated musical segment from Disney’s 1947 anthology film "Fun and Fancy Free," following the adventures of a circus bear who longs for freedom and love.
-
B.
Songololo
Songololo is a town in the western Democratic Republic of the Congo, situated near the border with Angola and known as a local transport and trade hub.
-
C.
Mbanderu
Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
-
D.
Bangangté
Bangangté is a prominent city in western Cameroon known as an important administrative and commercial center of the West Region.
-
E.
Welket Bungué
Welket Bungué is a Bissau-Guinean-born Portuguese actor known for his work in international cinema, including prominent roles in films such as "Crimes of the Future" and "Berlin Alexanderplatz."
- 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: Dor Bongo Triple: [Bongo language, hasAlternativeName, Dor Bongo]
Generated description
Dor Bongo is an alternative name for the Bongo language, a Central Sudanic language spoken primarily in South Sudan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dor Bongo Target entity description: Dor Bongo is an alternative name for the Bongo language, a Central Sudanic language spoken primarily in South Sudan.
-
A.
Bongo
Bongo is an animated musical segment from Disney’s 1947 anthology film "Fun and Fancy Free," following the adventures of a circus bear who longs for freedom and love.
-
B.
Songololo
Songololo is a town in the western Democratic Republic of the Congo, situated near the border with Angola and known as a local transport and trade hub.
-
C.
Mbanderu
Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
-
D.
Bangangté
Bangangté is a prominent city in western Cameroon known as an important administrative and commercial center of the West Region.
-
E.
Welket Bungué
Welket Bungué is a Bissau-Guinean-born Portuguese actor known for his work in international cinema, including prominent roles in films such as "Crimes of the Future" and "Berlin Alexanderplatz."
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799ed12d88190a4ad8c346d68f11f |
completed | April 9, 2026, 12:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d69c8b4819092614e83e855430e |
completed | April 19, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69e4307baca48190bbf82f8235d7e2c7 |
completed | April 19, 2026, 1:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4375eaf448190a17f8df1e83145e0 |
completed | April 19, 2026, 2:01 a.m. |
Created at: April 8, 2026, 9:27 p.m.