Triple

T31346850
Position Surface form Disambiguated ID Type / Status
Subject Papalote Children’s Museum E799469 entity
Predicate founder P104 FINISHED
Object María Asunción Aramburuzabala
María Asunción Aramburuzabala is a prominent Mexican businesswoman and billionaire investor, known as one of the country’s most influential entrepreneurs and philanthropists.
E1971076 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: María Asunción Aramburuzabala | Statement: [Papalote Children’s Museum, founder, María Asunción Aramburuzabala]
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: María Asunción Aramburuzabala
Triple: [Papalote Children’s Museum, founder, María Asunción Aramburuzabala]
Generated description
María Asunción Aramburuzabala is a prominent Mexican businesswoman and billionaire investor, known as one of the country’s most influential entrepreneurs and philanthropists.

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_69f224e51614819083141459a080e97c completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69f18afd48190bbbd54e517946499 completed May 3, 2026, 1:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79b2e53081909fd85a2c45d95dc3 completed June 12, 2026, 3:14 a.m.
NEDg Description generation batch_6a2b7a251de48190b92e41d64c9bbba9 completed June 12, 2026, 3:16 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7c1bf5e48190a12dd52a493a7c85 completed June 12, 2026, 3:25 a.m.
Created at: April 29, 2026, 9:17 p.m.