Triple
T7954676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bantu H languages |
E184701
|
entity |
| Predicate | hasNotableLanguage |
P7390
|
FINISHED |
| Object |
Lwena
Lwena is a Bantu language spoken primarily by the Luena (Lwena) people in parts of Angola and neighboring regions of Central Africa.
|
E702326
|
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: Lwena | Statement: [Bantu H languages, hasNotableLanguage, Lwena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lwena Context triple: [Bantu H languages, hasNotableLanguage, Lwena]
-
A.
Ngwena
Ngwena is the nickname of Emmerson Mnangagwa, the Zimbabwean politician and president known for his long-standing role in the country’s ruling party and post-Mugabe leadership.
-
B.
Lusiana
Lusiana is a small town in the Veneto region of northern Italy, known as the birthplace of Indian politician Sonia Gandhi.
-
C.
Lindi
Lindi is a feminine given name, typically used as a variant or diminutive of names like Linda.
-
D.
Lindi
Lindi is a coastal town in present-day Tanzania that historically served as an important port in the former German East Africa colony.
-
E.
Amba
Amba is a Hindu goddess, widely revered in western India as a fierce yet protective mother deity often worshipped during Navratri.
- 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: Lwena Triple: [Bantu H languages, hasNotableLanguage, Lwena]
Generated description
Lwena is a Bantu language spoken primarily by the Luena (Lwena) people in parts of Angola and neighboring regions of Central Africa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lwena Target entity description: Lwena is a Bantu language spoken primarily by the Luena (Lwena) people in parts of Angola and neighboring regions of Central Africa.
-
A.
Ngwena
Ngwena is the nickname of Emmerson Mnangagwa, the Zimbabwean politician and president known for his long-standing role in the country’s ruling party and post-Mugabe leadership.
-
B.
Lusiana
Lusiana is a small town in the Veneto region of northern Italy, known as the birthplace of Indian politician Sonia Gandhi.
-
C.
Lindi
Lindi is a feminine given name, typically used as a variant or diminutive of names like Linda.
-
D.
Lindi
Lindi is a coastal town in present-day Tanzania that historically served as an important port in the former German East Africa colony.
-
E.
Amba
Amba is a Hindu goddess, widely revered in western India as a fierce yet protective mother deity often worshipped during Navratri.
- 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_69ca8292cba881908a64427b938dac47 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b5f74308190aa63a22c3d5feacc |
completed | March 31, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe05d89a08190ae5bd4092d007442 |
completed | March 31, 2026, 2:55 p.m. |
| NEDg | Description generation | batch_69cbe43a45b48190b2bdc793f2bd3264 |
completed | March 31, 2026, 3:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc11c673d88190b2796fb6efac6b09 |
completed | March 31, 2026, 6:26 p.m. |
Created at: March 30, 2026, 5:11 p.m.