Triple

T27284203
Position Surface form Disambiguated ID Type / Status
Subject Kuban State Agrarian University E688422 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Humanities
The Faculty of Humanities is an academic division of Kuban State Agrarian University that focuses on disciplines such as languages, history, culture, and related humanistic studies.
 E1765884 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 Humanities | Statement: [Kuban State Agrarian University, hasFaculty, Faculty of Humanities]
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 Humanities
Triple: [Kuban State Agrarian University, hasFaculty, Faculty of Humanities]
Generated description
The Faculty of Humanities is an academic division of Kuban State Agrarian University that focuses on disciplines such as languages, history, culture, and related humanistic 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_69ef355998e08190bdff849e8f33adce completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f62753ec2481908aa814a112263356 completed May 2, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129ca3d3088190bdb2078fc6ab9a07 completed May 24, 2026, 6:37 a.m.
NEDg Description generation batch_6a129da51ce08190b85045a3d378c25f completed May 24, 2026, 6:41 a.m.
NED2 Entity disambiguation (via description) batch_6a129e4151208190995590e78cf35502 completed May 24, 2026, 6:44 a.m.
Created at: April 27, 2026, 11:10 a.m.