Triple

T36729985
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Business, University of Botswana E907301 entity
Predicate hasUnit P35 FINISHED
Object Department of Management
The Department of Management is an academic unit within the University of Botswana’s Faculty of Business that focuses on teaching and research in management and organizational studies.
 E2195854 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: Department of Management | Statement: [Faculty of Business, University of Botswana, hasUnit, Department of Management]
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: Department of Management
Triple: [Faculty of Business, University of Botswana, hasUnit, Department of Management]
Generated description
The Department of Management is an academic unit within the University of Botswana’s Faculty of Business that focuses on teaching and research in management and organizational studies.

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_69f76e746e4c8190a0d05cc6d57a643e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c8a319a8819094c55e6bc5517ba1 completed May 3, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a383f168c8190b4d33bdfe052eced completed June 23, 2026, 7:39 a.m.
NEDg Description generation batch_6a3a38e3e30481909d7058161151526d completed June 23, 2026, 7:42 a.m.
NED2 Entity disambiguation (via description) batch_6a3a4125ebd88190b0e2ceb7030c44f5 completed June 23, 2026, 8:17 a.m.
Created at: May 3, 2026, 4:12 p.m.