Triple
T12138393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Idomoid languages |
E289119
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Keana language
The Keana language is a lesser-known Idomoid language spoken by a small ethnic community in central Nigeria.
|
E969439
|
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: Keana language | Statement: [Idomoid languages, hasMember, Keana language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keana language Context triple: [Idomoid languages, hasMember, Keana language]
-
A.
Teke-Kega language
The Teke-Kega language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo and surrounding regions.
-
B.
Kaera language
The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
-
C.
Keapara language
The Keapara language is an Austronesian language of coastal Papua New Guinea spoken by the Keapara people in Central Province.
-
D.
Teiwa language
Teiwa language is a Papuan language spoken by the Teiwa people on Pantar Island in eastern Indonesia.
-
E.
Makasae language
The Makasae language is a Papuan language spoken primarily in the eastern part of Timor-Leste by the Makasae people.
- 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: Keana language Triple: [Idomoid languages, hasMember, Keana language]
Generated description
The Keana language is a lesser-known Idomoid language spoken by a small ethnic community in central Nigeria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Keana language Target entity description: The Keana language is a lesser-known Idomoid language spoken by a small ethnic community in central Nigeria.
-
A.
Teke-Kega language
The Teke-Kega language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo and surrounding regions.
-
B.
Kaera language
The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
-
C.
Keapara language
The Keapara language is an Austronesian language of coastal Papua New Guinea spoken by the Keapara people in Central Province.
-
D.
Teiwa language
Teiwa language is a Papuan language spoken by the Teiwa people on Pantar Island in eastern Indonesia.
-
E.
Makasae language
The Makasae language is a Papuan language spoken primarily in the eastern part of Timor-Leste by the Makasae people.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9158eef48819083bdce283a363414 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a7baee88190a32a5a3cd0b8a326 |
completed | May 2, 2026, 2:30 p.m. |
| NEDg | Description generation | batch_69f60bda16e48190af8abc0aa8ef41f0 |
completed | May 2, 2026, 2:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60cd51d34819099927fee476958ea |
completed | May 2, 2026, 2:40 p.m. |
Created at: April 8, 2026, 9:49 p.m.