Triple

T36680915
Position Surface form Disambiguated ID Type / Status
Subject University of Botswana E905677 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Education
The Faculty of Education at the University of Botswana is an academic division dedicated to training teachers, conducting educational research, and offering programs in pedagogy and educational leadership.
E905680 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: Faculty of Education | Statement: [University of Botswana, hasFaculty, Faculty of Education]
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: Faculty of Education
Triple: [University of Botswana, hasFaculty, Faculty of Education]
Generated description
The Faculty of Education at the University of Botswana is an academic division dedicated to training teachers, conducting educational research, and offering programs in pedagogy and educational leadership.

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_69f76e7011dc819082b324f18b756a1b completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c7bf4f50819082837d78e7e77941 completed May 3, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a381fb20c8190821db378015039b8 completed June 23, 2026, 7:39 a.m.
NEDg Description generation batch_6a3a3ae6cd10819097d341eb136791c8 completed June 23, 2026, 7:51 a.m.
NED2 Entity disambiguation (via description) batch_6a3a3cd93ddc81908e07cb3601c17678 completed June 23, 2026, 7:59 a.m.
Created at: May 3, 2026, 4:12 p.m.