Triple

T37383021
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Salamanca E928487 entity
Predicate hasMajorSeminary P16626 FINISHED
Object Seminary of Salamanca
The Seminary of Salamanca is a major Catholic ecclesiastical institution in Salamanca, Spain, dedicated to the academic and spiritual formation of future priests.
E2227505 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: Seminary of Salamanca | Statement: [Diocese of Salamanca, hasMajorSeminary, Seminary of Salamanca]
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: Seminary of Salamanca
Triple: [Diocese of Salamanca, hasMajorSeminary, Seminary of Salamanca]
Generated description
The Seminary of Salamanca is a major Catholic ecclesiastical institution in Salamanca, Spain, dedicated to the academic and spiritual formation of future priests.

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_69f76eb9e66881908534cf22d04c3b5a completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb8d19e5d881909c8872fa67cb8773 completed May 6, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a408242d9a88190b219d75149da6aed completed June 28, 2026, 2:09 a.m.
NEDg Description generation batch_6a4082c3d44c8190bcf3090e1fbcb069 completed June 28, 2026, 2:11 a.m.
NED2 Entity disambiguation (via description) batch_6a40839c76388190b3ac6bda25481e03 completed June 28, 2026, 2:14 a.m.
Created at: May 3, 2026, 4:16 p.m.