Triple

T25470415
Position Surface form Disambiguated ID Type / Status
Subject University of Southern Denmark E638288 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Humanities
The Faculty of Humanities at the University of Southern Denmark is an academic division dedicated to research and education in human culture, language, history, and related disciplines.
E1679579 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: [University of Southern Denmark, 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: [University of Southern Denmark, hasFaculty, Faculty of Humanities]
Generated description
The Faculty of Humanities at the University of Southern Denmark is an academic division dedicated to research and education in human culture, language, history, and related 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_69e75db9b964819096802dcf502e577e completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f7510dd08190bd6021cb5f2996d4 completed May 2, 2026, 1:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1089a295008190b2842385d1f8d473 completed May 22, 2026, 4:51 p.m.
NEDg Description generation batch_6a108a88dd5c8190ac1f024420860c32 completed May 22, 2026, 4:55 p.m.
NED2 Entity disambiguation (via description) batch_6a108b245e20819097efa96e0a3d866d completed May 22, 2026, 4:58 p.m.
Created at: April 21, 2026, 2:22 p.m.