Triple

T24146622
Position Surface form Disambiguated ID Type / Status
Subject Enrique Martín Morales E598403 entity
Predicate founded P104 FINISHED
Object Ricky Martin Foundation
The Ricky Martin Foundation is a nonprofit organization dedicated to advocating for the well-being of children around the world, with a strong focus on combating human trafficking and promoting education and social justice.
E1619719 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: Ricky Martin Foundation | Statement: [Enrique Martín Morales, founded, Ricky Martin Foundation]
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: Ricky Martin Foundation
Triple: [Enrique Martín Morales, founded, Ricky Martin Foundation]
Generated description
The Ricky Martin Foundation is a nonprofit organization dedicated to advocating for the well-being of children around the world, with a strong focus on combating human trafficking and promoting education and social justice.

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_69e288c9e488819093dd1acd91b08b8a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e00b00708190bcd1d0b855230378 completed April 29, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fad2c4ec88190aa5f21a659f60af4 completed May 22, 2026, 1:11 a.m.
NEDg Description generation batch_6a0fae10893c819092a3ecd95b6b9198 completed May 22, 2026, 1:14 a.m.
NED2 Entity disambiguation (via description) batch_6a0faf36d68881909ac3b5d6328efc8f completed May 22, 2026, 1:19 a.m.
Created at: April 17, 2026, 11:29 p.m.