Triple

T38488585
Position Surface form Disambiguated ID Type / Status
Subject Mole-Dagbani languages E917988 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Talni
Talni is a Gur language of the Mole-Dagbani branch spoken in parts of West Africa, particularly in northern Ghana.
E2271721 NE FINISHED

How this triple was built (2 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: Talni | Statement: [Mole-Dagbani languages, hasMemberLanguage, Talni]
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: Talni
Triple: [Mole-Dagbani languages, hasMemberLanguage, Talni]
Generated description
Talni is a Gur language of the Mole-Dagbani branch spoken in parts of West Africa, particularly in northern Ghana.

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_69f76e9894208190a129a553a60ca58c completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd23d627481908bfceb4dcf2634ef completed May 7, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41ccca5bc48190bdbb52b9f2aaa8ec completed June 29, 2026, 1:39 a.m.
NEDg Description generation batch_6a41d06939688190bc6e77dab6a8b5df completed June 29, 2026, 1:54 a.m.
NED2 Entity disambiguation (via description) batch_6a41d0e6dac88190b4f265d8dd825203 completed June 29, 2026, 1:56 a.m.
Created at: May 3, 2026, 4:31 p.m.