Triple

T38614675
Position Surface form Disambiguated ID Type / Status
Subject Katsina College E934579 entity
Predicate notableAlumnus P304 FINISHED
Object Aliyu Makama Bida
Aliyu Makama Bida was a prominent Nigerian statesman and traditional leader who played a significant role in the country’s early postcolonial political development.
E2278003 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: Aliyu Makama Bida | Statement: [Katsina College, notableAlumnus, Aliyu Makama Bida]
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: Aliyu Makama Bida
Triple: [Katsina College, notableAlumnus, Aliyu Makama Bida]
Generated description
Aliyu Makama Bida was a prominent Nigerian statesman and traditional leader who played a significant role in the country’s early postcolonial political development.

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_69f76eccd6d081909ccce171011739a1 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd97484848190ada7593631e400c6 completed May 7, 2026, 6:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41f447353481908292d76c8bf88b76 completed June 29, 2026, 4:27 a.m.
NEDg Description generation batch_6a41f582da6081909e324be0d1abc76e completed June 29, 2026, 4:33 a.m.
NED2 Entity disambiguation (via description) batch_6a41f61ba5a08190b74a5c3ec29c3665 completed June 29, 2026, 4:35 a.m.
Created at: May 3, 2026, 4:32 p.m.