Triple

T33636064
Position Surface form Disambiguated ID Type / Status
Subject Lund University Library E861695 entity
Predicate supportsFaculty P102842 FINISHED
Object Faculty of Science, Lund University
The Faculty of Science at Lund University is a major academic division specializing in natural sciences research and education at one of Sweden’s leading universities.
E851337 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 Science, Lund University | Statement: [Lund University Library, supportsFaculty, Faculty of Science, Lund University]
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 Science, Lund University
Triple: [Lund University Library, supportsFaculty, Faculty of Science, Lund University]
Generated description
The Faculty of Science at Lund University is a major academic division specializing in natural sciences research and education at one of Sweden’s leading universities.

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_69f34981c54c81909b33c3fa2208a52d completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_6a03809967388190bfdc58bda40bd3fc completed May 12, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3611b3b7b08190a2ac32c1f193c562 completed June 20, 2026, 4:06 a.m.
NEDg Description generation batch_6a3612623dec819088049f2540f38a38 completed June 20, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_6a36133c060c8190b1aa8fdc9017970d completed June 20, 2026, 4:12 a.m.
Created at: May 1, 2026, 1:42 a.m.