Triple

T36677102
Position Surface form Disambiguated ID Type / Status
Subject The Ballad of the Yorkshire Ripper E905571 entity
Predicate mainSubject P3 FINISHED
Object Peter Sutcliffe
Peter Sutcliffe, infamously known as the "Yorkshire Ripper," was an English serial killer who murdered multiple women across northern England in the 1970s and early 1980s.
E2193697 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: Peter Sutcliffe | Statement: [The Ballad of the Yorkshire Ripper, mainSubject, Peter Sutcliffe]
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: Peter Sutcliffe
Triple: [The Ballad of the Yorkshire Ripper, mainSubject, Peter Sutcliffe]
Generated description
Peter Sutcliffe, infamously known as the "Yorkshire Ripper," was an English serial killer who murdered multiple women across northern England in the 1970s and early 1980s.

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_69f76e7011dc819082b324f18b756a1b completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c7a3c6e08190b79f76bc3df441eb completed May 3, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a20dd836c8190b363a8ede247e929 completed June 23, 2026, 5:59 a.m.
NEDg Description generation batch_6a3a21e418248190a76af4dc9ae08403 completed June 23, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_6a3a227037a08190813771104b9abed5 completed June 23, 2026, 6:06 a.m.
Created at: May 3, 2026, 4:12 p.m.