Triple
T3258816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berom language |
E68361
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Kwi dialect
Kwi dialect is a regional variety of the Berom language spoken by Berom communities in parts of Plateau State, Nigeria.
|
E341608
|
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: Kwi dialect | Statement: [Berom language, hasDialect, Kwi dialect]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kwi dialect Context triple: [Berom language, hasDialect, Kwi dialect]
-
A.
Wama dialect
The Wama dialect is a regional variety of the Ashkun language spoken by Nuristani communities in eastern Afghanistan.
-
B.
Kuto-Kute dialect
The Kuto-Kute dialect is a regional variety of the Sasak language spoken on the island of Lombok in Indonesia.
-
C.
Nabua dialect
The Nabua dialect is a local variety of the Rinconada Bikol language spoken primarily in and around the municipality of Nabua in Camarines Sur, Philippines.
-
D.
Mitiaro dialect
The Mitiaro dialect is a regional variety of the Cook Islands Māori language spoken on the island of Mitiaro in the Cook Islands.
-
E.
Wipukpa dialect
The Wipukpa dialect is a regional variety of the Yavapai language traditionally spoken by a subgroup of the Yavapai people in central Arizona.
- 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: Kwi dialect Triple: [Berom language, hasDialect, Kwi dialect]
Generated description
Kwi dialect is a regional variety of the Berom language spoken by Berom communities in parts of Plateau State, Nigeria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kwi dialect Target entity description: Kwi dialect is a regional variety of the Berom language spoken by Berom communities in parts of Plateau State, Nigeria.
-
A.
Wama dialect
The Wama dialect is a regional variety of the Ashkun language spoken by Nuristani communities in eastern Afghanistan.
-
B.
Kuto-Kute dialect
The Kuto-Kute dialect is a regional variety of the Sasak language spoken on the island of Lombok in Indonesia.
-
C.
Nabua dialect
The Nabua dialect is a local variety of the Rinconada Bikol language spoken primarily in and around the municipality of Nabua in Camarines Sur, Philippines.
-
D.
Mitiaro dialect
The Mitiaro dialect is a regional variety of the Cook Islands Māori language spoken on the island of Mitiaro in the Cook Islands.
-
E.
Wipukpa dialect
The Wipukpa dialect is a regional variety of the Yavapai language traditionally spoken by a subgroup of the Yavapai people in central Arizona.
- 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_69ad858f74408190bcbd07f967cd7bd0 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adafa4f40c81909adfd0f7f568e3ce |
completed | March 8, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28ed941cc81909c35853e793d6ce5 |
completed | March 12, 2026, 10 a.m. |
| NEDg | Description generation | batch_69b2900805d08190afbda5ee5e984b71 |
completed | March 12, 2026, 10:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2ac4c52d48190a87b1e535c2e8a37 |
completed | March 12, 2026, 12:06 p.m. |
Created at: March 8, 2026, 3:09 p.m.