Triple

T27417255
Position Surface form Disambiguated ID Type / Status
Subject Universidad Industrial de Santander E692934 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Engineering
The Faculty of Engineering is a major academic division of the Universidad Industrial de Santander that offers engineering education and conducts research across multiple engineering disciplines.
E1776148 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 Engineering | Statement: [Universidad Industrial de Santander, hasFaculty, Faculty of Engineering]
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 Engineering
Triple: [Universidad Industrial de Santander, hasFaculty, Faculty of Engineering]
Generated description
The Faculty of Engineering is a major academic division of the Universidad Industrial de Santander that offers engineering education and conducts research across multiple engineering 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_69ef5208617081908f731d312e0fd1bc completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62d1a8c948190ab8629e1349a156f completed May 2, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbcd93e081909f646dbcd52d8666 completed May 24, 2026, 8:50 a.m.
NEDg Description generation batch_6a12bd0d87a88190a617ee64551f7d93 completed May 24, 2026, 8:55 a.m.
NED2 Entity disambiguation (via description) batch_6a12be3a604c8190887660a427cd9f2f completed May 24, 2026, 9 a.m.
Created at: April 27, 2026, 12:34 p.m.