Triple
T22296627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jarawan languages |
E551137
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Mbat language
The Mbat language is a lesser-known Jarawan Bantu language spoken by a small community in Nigeria.
|
E1529331
|
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: Mbat language | Statement: [Jarawan languages, hasMember, Mbat language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mbat language Context triple: [Jarawan languages, hasMember, Mbat language]
-
A.
Mbato language
The Mbato language is a Niger-Congo language spoken in parts of West Africa, belonging to the Potou–Tano branch of the Kwa language family.
-
B.
Mambae language
The Mambae language is an Austronesian language spoken primarily in East Timor, notable for its role in local identity and traditional culture.
-
C.
Babatana language
The Babatana language is an Oceanic language spoken by indigenous communities on Choiseul Island in the Solomon Islands.
-
D.
Maba language
The Maba language is an Afro-Asiatic language spoken primarily by the Maba people in eastern Chad and neighboring regions.
-
E.
Maba language
The Maba language is an Austronesian language spoken in eastern Indonesia, particularly in the Halmahera region of North Maluku.
- 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: Mbat language Triple: [Jarawan languages, hasMember, Mbat language]
Generated description
The Mbat language is a lesser-known Jarawan Bantu language spoken by a small community in Nigeria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mbat language Target entity description: The Mbat language is a lesser-known Jarawan Bantu language spoken by a small community in Nigeria.
-
A.
Mbato language
The Mbato language is a Niger-Congo language spoken in parts of West Africa, belonging to the Potou–Tano branch of the Kwa language family.
-
B.
Mambae language
The Mambae language is an Austronesian language spoken primarily in East Timor, notable for its role in local identity and traditional culture.
-
C.
Babatana language
The Babatana language is an Oceanic language spoken by indigenous communities on Choiseul Island in the Solomon Islands.
-
D.
Maba language
The Maba language is an Afro-Asiatic language spoken primarily by the Maba people in eastern Chad and neighboring regions.
-
E.
Maba language
The Maba language is an Austronesian language spoken in eastern Indonesia, particularly in the Halmahera region of North Maluku.
- 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_69e11e45fb848190a1b2ae21296e3a5f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15720fba0819080f6c96f6df4f1e0 |
completed | April 29, 2026, 12:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0acc9609788190a1e7306a47a3fb56 |
completed | May 18, 2026, 8:23 a.m. |
| NEDg | Description generation | batch_6a0acd67a4c88190bf64d4ecad0491b9 |
completed | May 18, 2026, 8:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0acdcc02ac8190a35b572701410c80 |
completed | May 18, 2026, 8:29 a.m. |
Created at: April 16, 2026, 8:41 p.m.