Triple

T36339855
Position Surface form Disambiguated ID Type / Status
Subject Institute of Desertification Studies E894882 entity
Predicate affiliation P10 FINISHED
Object Faculty of the University of Khartoum
The Faculty of the University of Khartoum is a major academic division of Sudan’s leading public university, encompassing teaching and research across multiple disciplines.
 E2188734 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 the University of Khartoum | Statement: [Institute of Desertification Studies, affiliation, Faculty of the University of Khartoum]
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 the University of Khartoum
Triple: [Institute of Desertification Studies, affiliation, Faculty of the University of Khartoum]
Generated description
The Faculty of the University of Khartoum is a major academic division of Sudan’s leading public university, encompassing teaching and research across multiple 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_69f76e4e90148190b02fe52593c70b5b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7ba9cd6408190ba500b3e3e697275 completed May 3, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3f69f294308190aec30937221601de completed June 27, 2026, 6:13 a.m.
NEDg Description generation batch_6a3f6cc043bc8190a083d180a2f8380b completed June 27, 2026, 6:25 a.m.
NED2 Entity disambiguation (via description) batch_6a3f6d1afc288190a482cc40a9193aa0 completed June 27, 2026, 6:26 a.m.
Created at: May 3, 2026, 4:09 p.m.