Triple

T27348212
Position Surface form Disambiguated ID Type / Status
Subject IPN E684285 entity
Predicate foundedBy P104 FINISHED
Object Juan de Dios Bátiz
Juan de Dios Bátiz was a Mexican engineer, educator, and politician best known as a key founder and promoter of the National Polytechnic Institute (IPN), one of Mexico’s leading public technological universities.
E1767907 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: Juan de Dios Bátiz | Statement: [IPN, foundedBy, Juan de Dios Bátiz]
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: Juan de Dios Bátiz
Triple: [IPN, foundedBy, Juan de Dios Bátiz]
Generated description
Juan de Dios Bátiz was a Mexican engineer, educator, and politician best known as a key founder and promoter of the National Polytechnic Institute (IPN), one of Mexico’s leading public technological universities.

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_69ef1480a76481908684256ddd5bfda3 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62ba5a110819092fe773ade8fec2e completed May 2, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129ccb46588190b076fc5c8475879b completed May 24, 2026, 6:38 a.m.
NEDg Description generation batch_6a129dc563e081909b6e07e29aad6ddb completed May 24, 2026, 6:42 a.m.
NED2 Entity disambiguation (via description) batch_6a129e5f7e348190af4a279de8ef8caa completed May 24, 2026, 6:44 a.m.
Created at: April 27, 2026, 11:46 a.m.