Triple

T34756229
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of Quito E1001930 entity
Predicate describedBy P264 FINISHED
Object Juan de Velasco
Juan de Velasco was an 18th-century Ecuadorian Jesuit priest, historian, and scholar best known for his influential historical work on the Kingdom of Quito and the origins of what is now Ecuador.
E2113943 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 Velasco | Statement: [Kingdom of Quito, describedBy, Juan de Velasco]
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 Velasco
Triple: [Kingdom of Quito, describedBy, Juan de Velasco]
Generated description
Juan de Velasco was an 18th-century Ecuadorian Jesuit priest, historian, and scholar best known for his influential historical work on the Kingdom of Quito and the origins of what is now Ecuador.

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_69f76db0fb30819096709d43f9a1f45f completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f779f06f788190874bd90303c64df7 completed May 3, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a376f9cd7d4819089face711b92113a completed June 21, 2026, 4:59 a.m.
NEDg Description generation batch_6a37715f5fe48190b3e55077244032ce completed June 21, 2026, 5:06 a.m.
NED2 Entity disambiguation (via description) batch_6a37722ef0b48190b44093b10978145a completed June 21, 2026, 5:10 a.m.
Created at: May 3, 2026, 3:59 p.m.