Triple

T30408918
Position Surface form Disambiguated ID Type / Status
Subject University of Alicante E773554 entity
Predicate hasLibrary P35 FINISHED
Object University of Alicante Library
The University of Alicante Library is the main academic library system of the University of Alicante, providing collections, study spaces, and research support services to its students and faculty.
E1912180 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: University of Alicante Library | Statement: [University of Alicante, hasLibrary, University of Alicante Library]
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: University of Alicante Library
Triple: [University of Alicante, hasLibrary, University of Alicante Library]
Generated description
The University of Alicante Library is the main academic library system of the University of Alicante, providing collections, study spaces, and research support services to its students and faculty.

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_69f22490b8b48190ab10c886a8d58c89 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68621f9fc81908af56eb9716cbef9 completed May 2, 2026, 11:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27895c72c881909a944eb59c90d0ec completed June 9, 2026, 3:32 a.m.
NEDg Description generation batch_6a278b337b0c8190b870deac9a0be21a completed June 9, 2026, 3:40 a.m.
NED2 Entity disambiguation (via description) batch_6a278bb7c0908190999f35c9918d8d6c completed June 9, 2026, 3:42 a.m.
Created at: April 29, 2026, 8:04 p.m.