Triple

T25192735
Position Surface form Disambiguated ID Type / Status
Subject Bantu zone L E630914 entity
Predicate hasLanguage P15 FINISHED
Object Binji language
The Binji language is a lesser-known Bantu language spoken by the Binji people in the Democratic Republic of the Congo.
E1670952 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: Binji language | Statement: [Bantu zone L, hasLanguage, Binji language]
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: Binji language
Triple: [Bantu zone L, hasLanguage, Binji language]
Generated description
The Binji language is a lesser-known Bantu language spoken by the Binji people in the Democratic Republic of the Congo.

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_69e75a8a6d088190ba1e82a4345225e7 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46e113b448190a53554695d9441b4 completed May 1, 2026, 9:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067cc23f081908a192d5558f779c9 completed May 22, 2026, 2:27 p.m.
NEDg Description generation batch_6a1068d5ff248190b9efb77366147c26 completed May 22, 2026, 2:31 p.m.
NED2 Entity disambiguation (via description) batch_6a1069d0ba8c81908b38818567784552 completed May 22, 2026, 2:36 p.m.
Created at: April 21, 2026, 12:45 p.m.