Triple

T23535272
Position Surface form Disambiguated ID Type / Status
Subject All Quiet on the Western Front (1979 film) E576682 entity
Predicate starredActor P5563 FINISHED
Object Michael Sheard
Michael Sheard was a British character actor best known for his frequent villainous roles in film and television, including appearances in the Star Wars franchise and the TV series Grange Hill.
E1618185 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: Michael Sheard | Statement: [All Quiet on the Western Front (1979 film), starredActor, Michael Sheard]
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: Michael Sheard
Triple: [All Quiet on the Western Front (1979 film), starredActor, Michael Sheard]
Generated description
Michael Sheard was a British character actor best known for his frequent villainous roles in film and television, including appearances in the Star Wars franchise and the TV series Grange Hill.

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_69e245f5a8848190a2ba42e271c6c31f completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ae164f348190a6bde1a0dfc66389 completed April 29, 2026, 7:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f9621460881908863afc129357025 completed May 21, 2026, 11:32 p.m.
NEDg Description generation batch_6a0f973823ac819092f241755fe86bf2 completed May 21, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_6a0f981441b08190a0076042748d92ea completed May 21, 2026, 11:41 p.m.
Created at: April 17, 2026, 6:10 p.m.