Triple

T33407325
Position Surface form Disambiguated ID Type / Status
Subject Jerry Brudos E855471 entity
Predicate victim P870 FINISHED
Object Linda Saley
Linda Saley was a young woman in Oregon who became one of the murder victims of serial killer Jerry Brudos in the late 1960s.
E2285500 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: Linda Saley | Statement: [Jerry Brudos, victim, Linda Saley]
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: Linda Saley
Triple: [Jerry Brudos, victim, Linda Saley]
Generated description
Linda Saley was a young woman in Oregon who became one of the murder victims of serial killer Jerry Brudos in the late 1960s.

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_69f3496f04a08190804e56ac5098b8e4 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e430cfd88190acd235d324d9298a completed May 3, 2026, 5:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a45f1e5484c819080b4fa4809cc17b2 completed July 2, 2026, 5:06 a.m.
NEDg Description generation batch_6a45f62ded008190a5ac436d6af1a661 completed July 2, 2026, 5:25 a.m.
NED2 Entity disambiguation (via description) batch_6a45f73fb2d48190b50aac074636e7a4 completed July 2, 2026, 5:29 a.m.
Created at: May 1, 2026, 1:36 a.m.