Triple

T28139923

Position	Surface form	Disambiguated ID	Type / Status
Subject	Alberto Ríos	`E714315`	entity
Predicate	name	`P16`	FINISHED
Object	Alberto Álvaro Ríos Alberto Álvaro Ríos is an American poet, short story writer, and Arizona’s first state poet laureate, known for works that explore borderland culture and personal history.	`E1805076`	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: Alberto Álvaro Ríos | Statement: [Alberto Ríos, name, Alberto Álvaro Ríos]

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: Alberto Álvaro Ríos
Triple: [Alberto Ríos, name, Alberto Álvaro Ríos]

Generated description

Alberto Álvaro Ríos is an American poet, short story writer, and Arizona’s first state poet laureate, known for works that explore borderland culture and personal history.

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_69efd6af156c81908f50c2cd7db0e1ef`	completed	April 27, 2026, 9:35 p.m.
NER	Named-entity recognition	`batch_69f64133fc4081908f9d682dcfdbd517`	completed	May 2, 2026, 6:23 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a15d7a249808190a822fb949af996ea`	completed	May 26, 2026, 5:25 p.m.
NEDg	Description generation	`batch_6a15dad9fac881908a639795ac0a908b`	completed	May 26, 2026, 5:39 p.m.
NED2	Entity disambiguation (via description)	`batch_6a15db82ef1481908402a27126482289`	completed	May 26, 2026, 5:42 p.m.

Created at: April 27, 2026, 9:52 p.m.