Triple

T26443356
Position Surface form Disambiguated ID Type / Status
Subject Sandoval E665145 entity
Predicate hasNotableBearer P458 FINISHED
Object Jorge Sandoval
Jorge Sandoval is a personal name shared by multiple individuals, most commonly found in Spanish-speaking countries and associated with various professionals in fields such as sports, politics, and the arts.
 E1757372 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: Jorge Sandoval | Statement: [Sandoval, hasNotableBearer, Jorge Sandoval]
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: Jorge Sandoval
Triple: [Sandoval, hasNotableBearer, Jorge Sandoval]
Generated description
Jorge Sandoval is a personal name shared by multiple individuals, most commonly found in Spanish-speaking countries and associated with various professionals in fields such as sports, politics, and the arts.

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_69ee883c851881909e2ab04efbb3c5fe completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f6121d00d48190b64b88a7d75c6e3b completed May 2, 2026, 3:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1247d654248190aea0c9bd2ff72a61 completed May 24, 2026, 12:35 a.m.
NEDg Description generation batch_6a1248bb58a48190ae84e7b538b10503 completed May 24, 2026, 12:39 a.m.
NED2 Entity disambiguation (via description) batch_6a124973e3c88190898b0cece69419b3 completed May 24, 2026, 12:42 a.m.
Created at: April 27, 2026, midnight