Triple

T27519828
Position Surface form Disambiguated ID Type / Status
Subject Reșița E694674 entity
Predicate hasHigherEducationInstitution P113 FINISHED
Object Eftimie Murgu University of Reșița
Eftimie Murgu University of Reșița is a Romanian public university located in the city of Reșița, offering a range of academic programs and research activities.
E1777506 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: Eftimie Murgu University of Reșița | Statement: [Reșița, hasHigherEducationInstitution, Eftimie Murgu University of Reșița]
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: Eftimie Murgu University of Reșița
Triple: [Reșița, hasHigherEducationInstitution, Eftimie Murgu University of Reșița]
Generated description
Eftimie Murgu University of Reșița is a Romanian public university located in the city of Reșița, offering a range of academic programs and research activities.

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_69ef538550208190aa9de8e2cb260d93 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f2accf081908b50f8473deda2de completed May 2, 2026, 5:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12c5ad2cf881908e983f96b2cb87b1 completed May 24, 2026, 9:32 a.m.
NEDg Description generation batch_6a12c6d263e081908a23dfd19fba2df2 completed May 24, 2026, 9:37 a.m.
NED2 Entity disambiguation (via description) batch_6a12c79229e08190830d0c8f139a228c completed May 24, 2026, 9:40 a.m.
Created at: April 27, 2026, 1:20 p.m.