Triple

T28413246
Position Surface form Disambiguated ID Type / Status
Subject Universidad Distrital Francisco José de Caldas E719724 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Technology
The Faculty of Technology is an academic division of Universidad Distrital Francisco José de Caldas that focuses on technological and engineering education and research.
E1821222 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 Technology | Statement: [Universidad Distrital Francisco José de Caldas, hasFaculty, Faculty of Technology]
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 Technology
Triple: [Universidad Distrital Francisco José de Caldas, hasFaculty, Faculty of Technology]
Generated description
The Faculty of Technology is an academic division of Universidad Distrital Francisco José de Caldas that focuses on technological and engineering education and research.

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_69eff6f0f37c8190b37bc6fab08a9449 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64dbe401081909ea87d252a09101d completed May 2, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac36bbe48190a6aaf93406fd0294 completed May 31, 2026, 9:46 p.m.
NEDg Description generation batch_6a1cacb5263481909564ae00060c003e completed May 31, 2026, 9:48 p.m.
NED2 Entity disambiguation (via description) batch_6a1cad97f90c819090f2ae899ebb32d9 completed May 31, 2026, 9:52 p.m.
Created at: April 28, 2026, 1:28 a.m.