Triple

T28402483
Position Surface form Disambiguated ID Type / Status
Subject University of Food Technologies – Plovdiv E719426 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Food Engineering
The Faculty of Food Engineering is an academic division specializing in the science, technology, and engineering of food production and processing at the University of Food Technologies in Plovdiv.
 E1818576 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 Food Engineering | Statement: [University of Food Technologies – Plovdiv, hasFaculty, Faculty of Food Engineering]
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 Food Engineering
Triple: [University of Food Technologies – Plovdiv, hasFaculty, Faculty of Food Engineering]
Generated description
The Faculty of Food Engineering is an academic division specializing in the science, technology, and engineering of food production and processing at the University of Food Technologies in Plovdiv.

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_69eff6efd1b08190ae3cefd4f11388a2 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64d6d0b908190a272f7e51d6be67c completed May 2, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16417856b48190a0e3e93adfbef02f completed May 27, 2026, 12:57 a.m.
NEDg Description generation batch_6a1642b38cfc81909cdd508d4f2969b7 completed May 27, 2026, 1:02 a.m.
NED2 Entity disambiguation (via description) batch_6a16434f165c819081ea70b81354a508 completed May 27, 2026, 1:05 a.m.
Created at: April 28, 2026, 1:21 a.m.