Triple

T38242475
Position Surface form Disambiguated ID Type / Status
Subject Felix Westen E1013801 entity
Predicate loyalTo P1201 FINISHED
Object Victor Salazar
Victor Salazar is the central character of the TV series "Love, Victor," a gay Latino teenager navigating high school, family expectations, and his journey of self-discovery.
E1101872 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: Victor Salazar | Statement: [Felix Westen, loyalTo, Victor Salazar]
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: Victor Salazar
Triple: [Felix Westen, loyalTo, Victor Salazar]
Generated description
Victor Salazar is the central character of the TV series "Love, Victor," a gay Latino teenager navigating high school, family expectations, and his journey of self-discovery.

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_69f76dd7e89c8190b7866bc85aea521b completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcb180f138819090972487d009ff28 completed May 7, 2026, 3:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5bf7d9edf081908bdea37ba76b292e completed July 18, 2026, 10:02 p.m.
NEDg Description generation batch_6a5bf87502c481908c674540f2536faa completed July 18, 2026, 10:04 p.m.
NED2 Entity disambiguation (via description) batch_6a5bf8ce6bd08190be5b190cf914a30e completed July 18, 2026, 10:06 p.m.
Created at: May 3, 2026, 4:30 p.m.