Triple
T17838419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maba people |
E445454
|
entity |
| Predicate | ethnicity |
P194
|
FINISHED |
| Object |
Maba
Maba are an ethnic group primarily inhabiting eastern Chad and western Sudan, known for their distinct language and cultural traditions.
|
E1292467
|
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: Maba | Statement: [Maba people, ethnicity, Maba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maba Context triple: [Maba people, ethnicity, Maba]
-
A.
Mabayo
Mabayo is a coastal barangay in the municipality of Morong in the province of Bataan, Philippines.
-
B.
Matabaan
Matabaan is a town in central Somalia that serves as one of the urban centers within the federal member state of Hirshabelle.
-
C.
Mbyá
Mbyá are an Indigenous Guaraní-speaking people of South America, primarily living in regions of Paraguay, Brazil, and Argentina, with a distinct language, culture, and spiritual tradition.
-
D.
Mabika
Mabika is the surname of Mwadi Mabika, a notable Congolese basketball player who competed internationally and in the WNBA.
-
E.
Mandeali
Mandeali is an Indo-Aryan language spoken primarily in the Mandi district of Himachal Pradesh in northern India.
- 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: Maba Triple: [Maba people, ethnicity, Maba]
Generated description
Maba are an ethnic group primarily inhabiting eastern Chad and western Sudan, known for their distinct language and cultural traditions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maba Target entity description: Maba are an ethnic group primarily inhabiting eastern Chad and western Sudan, known for their distinct language and cultural traditions.
-
A.
Mabayo
Mabayo is a coastal barangay in the municipality of Morong in the province of Bataan, Philippines.
-
B.
Matabaan
Matabaan is a town in central Somalia that serves as one of the urban centers within the federal member state of Hirshabelle.
-
C.
Mbyá
Mbyá are an Indigenous Guaraní-speaking people of South America, primarily living in regions of Paraguay, Brazil, and Argentina, with a distinct language, culture, and spiritual tradition.
-
D.
Mabika
Mabika is the surname of Mwadi Mabika, a notable Congolese basketball player who competed internationally and in the WNBA.
-
E.
Mandeali
Mandeali is an Indo-Aryan language spoken primarily in the Mandi district of Himachal Pradesh in northern India.
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48d29830c81909fa3ef5a352921b8 |
completed | April 19, 2026, 8:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a030c5a9324819096c4d43d493ddbd4 |
completed | May 12, 2026, 11:17 a.m. |
| NEDg | Description generation | batch_6a030d85e91481908e6afd4a83d78ce8 |
completed | May 12, 2026, 11:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a030e6412dc81908b392bdf47934230 |
completed | May 12, 2026, 11:26 a.m. |
Created at: April 10, 2026, 10:16 a.m.