Triple

T37253575
Position Surface form Disambiguated ID Type / Status
Subject Resident Evil: Revelations E924060 entity
Predicate character P662 FINISHED
Object Raymond Vester
Raymond Vester is a covert operative and key supporting character in the survival horror game Resident Evil: Revelations, known for his ambiguous loyalties and distinctive red hair and mask.
E2219388 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: Raymond Vester | Statement: [Resident Evil: Revelations, character, Raymond Vester]
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: Raymond Vester
Triple: [Resident Evil: Revelations, character, Raymond Vester]
Generated description
Raymond Vester is a covert operative and key supporting character in the survival horror game Resident Evil: Revelations, known for his ambiguous loyalties and distinctive red hair and mask.

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_69f76eaabb4c819093b751b139dad551 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb3729c6e481909a375336128176f5 completed May 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4043d3bb4c81908b62cff2c9f27271 completed June 27, 2026, 9:42 p.m.
NEDg Description generation batch_6a4044fd17208190b590493419679ef1 completed June 27, 2026, 9:47 p.m.
NED2 Entity disambiguation (via description) batch_6a4046ed8adc81909bb53bad47859232 completed June 27, 2026, 9:55 p.m.
Created at: May 3, 2026, 4:15 p.m.