Triple

T23962157
Position Surface form Disambiguated ID Type / Status
Subject Gualtar campus E603955 entity
Predicate hosts P186 FINISHED
Object Institute of Education (University of Minho)
The Institute of Education of the University of Minho is an academic unit in Portugal dedicated to research, training, and innovation in education and teacher preparation.
E1610077 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: Institute of Education (University of Minho) | Statement: [Gualtar campus, hosts, Institute of Education (University of Minho)]
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: Institute of Education (University of Minho)
Triple: [Gualtar campus, hosts, Institute of Education (University of Minho)]
Generated description
The Institute of Education of the University of Minho is an academic unit in Portugal dedicated to research, training, and innovation in education and teacher preparation.

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_69e2954222288190a7323554d0cca8d7 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d0dac8e081908286e8d8d30784ee completed April 29, 2026, 9:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f765cc3508190b5f745ed932f7eab completed May 21, 2026, 9:17 p.m.
NEDg Description generation batch_6a0f770a063c81909f356346c9c521ad completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f782b47c08190a221c196ddc9d566 completed May 21, 2026, 9:24 p.m.
Created at: April 17, 2026, 9:23 p.m.