Triple

T2662899
Position Surface form Disambiguated ID Type / Status
Subject Benue–Congo languages E54765 entity
Predicate hasNotableLanguage P7390 FINISHED
Object Bini language
Bini language is an Edoid language of southern Nigeria, primarily spoken by the Edo (Bini) people around Benin City.
E286632 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: Bini language | Statement: [Benue–Congo languages, hasNotableLanguage, Bini language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bini language
Context triple: [Benue–Congo languages, hasNotableLanguage, Bini language]
  • A. Bintauna language
    The Bintauna language is an Austronesian language spoken by the Bintauna people in North Sulawesi, Indonesia.
  • B. Baniwa language
    Baniwa is an Arawakan Indigenous language spoken primarily along the Rio Negro in northwestern Brazil, as well as in parts of Colombia and Venezuela.
  • C. Bajelani language
    The Bajelani language is a lesser-known Northwestern Iranian language spoken primarily by Kurdish communities in parts of Iraq and Iran.
  • D. Bongo language
    The Bongo language is a Central Sudanic language spoken by the Bongo people of South Sudan.
  • E. Banda-Ndélé language
    The Banda-Ndélé language is a Central Sudanic language spoken by the Banda people, primarily in the Central African Republic.
  • 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: Bini language
Triple: [Benue–Congo languages, hasNotableLanguage, Bini language]
Generated description
Bini language is an Edoid language of southern Nigeria, primarily spoken by the Edo (Bini) people around Benin City.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bini language
Target entity description: Bini language is an Edoid language of southern Nigeria, primarily spoken by the Edo (Bini) people around Benin City.
  • A. Bintauna language
    The Bintauna language is an Austronesian language spoken by the Bintauna people in North Sulawesi, Indonesia.
  • B. Baniwa language
    Baniwa is an Arawakan Indigenous language spoken primarily along the Rio Negro in northwestern Brazil, as well as in parts of Colombia and Venezuela.
  • C. Bajelani language
    The Bajelani language is a lesser-known Northwestern Iranian language spoken primarily by Kurdish communities in parts of Iraq and Iran.
  • D. Bongo language
    The Bongo language is a Central Sudanic language spoken by the Bongo people of South Sudan.
  • E. Banda-Ndélé language
    The Banda-Ndélé language is a Central Sudanic language spoken by the Banda people, primarily in the Central African Republic.
  • 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_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd96b9f1c8190a8a9460ca88a9aaf completed March 7, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98d9d7148190841bac9589a3815b completed March 10, 2026, 4:06 a.m.
NEDg Description generation batch_69af99c237548190838559ccac95f1c5 completed March 10, 2026, 4:10 a.m.
NED2 Entity disambiguation (via description) batch_69af9a5a8ee8819080d49f13e5b4eab1 completed March 10, 2026, 4:13 a.m.
Created at: March 6, 2026, 9:53 p.m.