Triple
T3991562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bulu language |
E87000
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Yembana
Yembana is a dialect of the Bulu language, a Bantu language spoken primarily in southern Cameroon.
|
E407095
|
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: Yembana | Statement: [Bulu language, hasDialect, Yembana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yembana Context triple: [Bulu language, hasDialect, Yembana]
-
A.
Eyamba
Eyamba is a prominent clan of the Efik people of southeastern Nigeria, historically associated with leadership and influence in the Old Calabar region.
-
B.
Nembe
Nembe is an Ijaw subgroup and town in Bayelsa State, Nigeria, known historically as a coastal trading center in the Niger Delta.
-
C.
Kandia
Kandia is a remote valley and settlement area located within Pakistan’s Kohistan mountain ranges, known for its rugged terrain and isolated communities.
-
D.
Yassa
Yassa was the codified legal and administrative code traditionally attributed to Genghis Khan that governed the Mongol Empire and its successor states.
-
E.
Tamba
Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
- 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: Yembana Triple: [Bulu language, hasDialect, Yembana]
Generated description
Yembana is a dialect of the Bulu language, a Bantu language spoken primarily in southern Cameroon.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yembana Target entity description: Yembana is a dialect of the Bulu language, a Bantu language spoken primarily in southern Cameroon.
-
A.
Eyamba
Eyamba is a prominent clan of the Efik people of southeastern Nigeria, historically associated with leadership and influence in the Old Calabar region.
-
B.
Nembe
Nembe is an Ijaw subgroup and town in Bayelsa State, Nigeria, known historically as a coastal trading center in the Niger Delta.
-
C.
Kandia
Kandia is a remote valley and settlement area located within Pakistan’s Kohistan mountain ranges, known for its rugged terrain and isolated communities.
-
D.
Yassa
Yassa was the codified legal and administrative code traditionally attributed to Genghis Khan that governed the Mongol Empire and its successor states.
-
E.
Tamba
Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa02ed6881908e31d342413fed26 |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c50f348819090ebfd8b5192c819 |
completed | March 14, 2026, 11:53 a.m. |
| NEDg | Description generation | batch_69b550142cb88190b797ea327cff136e |
completed | March 14, 2026, 12:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5507641408190ab3407faf0aee807 |
completed | March 14, 2026, 12:11 p.m. |
Created at: March 9, 2026, 3:33 p.m.