Triple

T27571053
Position Surface form Disambiguated ID Type / Status
Subject University of Swat E696034 entity
Predicate hasDepartment P35 FINISHED
Object Department of Management Sciences
The Department of Management Sciences at the University of Swat is an academic unit that offers education and research programs in business, management, and related disciplines.
E1777347 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 Sciences | Statement: [University of Swat, hasDepartment, Department of Management Sciences]
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 Sciences
Triple: [University of Swat, hasDepartment, Department of Management Sciences]
Generated description
The Department of Management Sciences at the University of Swat is an academic unit that offers education and research programs in business, management, and related disciplines.

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_69ef53891af88190a193c5e2a1dac9b1 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62fec821081909ae17c4c3bdcae19 completed May 2, 2026, 5:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12c5d2c4c08190943b42de9a8d2fe4 completed May 24, 2026, 9:33 a.m.
NEDg Description generation batch_6a12c6431ff8819092864b074cc494b8 completed May 24, 2026, 9:34 a.m.
NED2 Entity disambiguation (via description) batch_6a12c6c3a8fc819083942c89ff00352b completed May 24, 2026, 9:37 a.m.
Created at: April 27, 2026, 1:43 p.m.