Triple

T25848435
Position Surface form Disambiguated ID Type / Status
Subject West University of Timișoara E651133 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Music and Theatre
The Faculty of Music and Theatre is an academic unit specializing in higher education and professional training in music and performing arts within the West University of Timișoara.
 E1701495 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 Music and Theatre | Statement: [West University of Timișoara, hasFaculty, Faculty of Music and Theatre]
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 Music and Theatre
Triple: [West University of Timișoara, hasFaculty, Faculty of Music and Theatre]
Generated description
The Faculty of Music and Theatre is an academic unit specializing in higher education and professional training in music and performing arts within the West University of Timișoara.

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_69e7ab39035c8190be15c8aaee1bb858 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f60239fb6881908503759ddd6b3fb1 completed May 2, 2026, 1:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecae1f2c8190a0b63bb0798df768 completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10ee2510588190a304a6c042436217 completed May 23, 2026, midnight
NED2 Entity disambiguation (via description) batch_6a10f04c3c4c8190bd0084b6b1b9e7a7 completed May 23, 2026, 12:09 a.m.
Created at: April 22, 2026, 7:57 a.m.