Triple
T11302691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voltaic languages |
E267634
|
entity |
| Predicate | hasMemberLanguage |
P7390
|
FINISHED |
| Object |
Nawdm
Nawdm is a Gur (Voltaic) language spoken primarily in northern Togo and neighboring regions of West Africa.
|
E917986
|
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: Nawdm | Statement: [Voltaic languages, hasMemberLanguage, Nawdm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nawdm Context triple: [Voltaic languages, hasMemberLanguage, Nawdm]
-
A.
Nawar
Nawar are a traditionally itinerant ethnic group of the Middle East, culturally and linguistically related to the Dom people and often associated with peripatetic trades and marginalized social status.
-
B.
Nafe
Nafe is an indigenous Oceanic language spoken in Vanuatu.
-
C.
Nawbahar
Nawbahar was the mother of Mahmud of Ghazni, the prominent 11th-century sultan who founded the Ghaznavid Empire in present-day Afghanistan and northern India.
-
D.
Nawat
Nawat is an indigenous Uto-Aztecan language of El Salvador, traditionally spoken by the Pipil people and now the focus of revitalization efforts.
-
E.
Navedenga
Navedenga is a large-scale, immersive installation by Brazilian artist Ernesto Neto that envelops viewers in a sensorial environment of organic forms, textiles, and spices.
- 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: Nawdm Triple: [Voltaic languages, hasMemberLanguage, Nawdm]
Generated description
Nawdm is a Gur (Voltaic) language spoken primarily in northern Togo and neighboring regions of West Africa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nawdm Target entity description: Nawdm is a Gur (Voltaic) language spoken primarily in northern Togo and neighboring regions of West Africa.
-
A.
Nawar
Nawar are a traditionally itinerant ethnic group of the Middle East, culturally and linguistically related to the Dom people and often associated with peripatetic trades and marginalized social status.
-
B.
Nafe
Nafe is an indigenous Oceanic language spoken in Vanuatu.
-
C.
Nawbahar
Nawbahar was the mother of Mahmud of Ghazni, the prominent 11th-century sultan who founded the Ghaznavid Empire in present-day Afghanistan and northern India.
-
D.
Nawat
Nawat is an indigenous Uto-Aztecan language of El Salvador, traditionally spoken by the Pipil people and now the focus of revitalization efforts.
-
E.
Navedenga
Navedenga is a large-scale, immersive installation by Brazilian artist Ernesto Neto that envelops viewers in a sensorial environment of organic forms, textiles, and spices.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a5c3788190ba54eda514b97903 |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a57366081908a05fc52c5d4074c |
completed | April 19, 2026, 5:01 p.m. |
| NEDg | Description generation | batch_69e510f9edb4819097e9fa1ce85504ed |
completed | April 19, 2026, 5:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e516ac8dec81909c9c1eece372189e |
completed | April 19, 2026, 5:53 p.m. |
Created at: April 8, 2026, 9:32 p.m.