Triple

T26171932
Position Surface form Disambiguated ID Type / Status
Subject Morris Maaskov E654425 entity
Predicate notableRole P22 FINISHED
Object Mr. Jaeckel in The Great Dictator
Mr. Jaeckel in *The Great Dictator* is a supporting character in Charlie Chaplin’s 1940 satirical film about dictatorship and fascism.
 E1712401 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: Mr. Jaeckel in The Great Dictator | Statement: [Morris Maaskov, notableRole, Mr. Jaeckel in The Great Dictator]
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: Mr. Jaeckel in The Great Dictator
Triple: [Morris Maaskov, notableRole, Mr. Jaeckel in The Great Dictator]
Generated description
Mr. Jaeckel in *The Great Dictator* is a supporting character in Charlie Chaplin’s 1940 satirical film about dictatorship and fascism.

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_69ee5b45873c81909499203612d05d07 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60c4485748190aff17798bca51406 completed May 2, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11277b7bac81908799caea4b493660 completed May 23, 2026, 4:05 a.m.
NEDg Description generation batch_6a114ddf95c8819090e2e2d6fa5e3ac6 completed May 23, 2026, 6:49 a.m.
NED2 Entity disambiguation (via description) batch_6a114e96c4108190ba472aabc8d5d9f6 completed May 23, 2026, 6:52 a.m.
Created at: April 26, 2026, 8:35 p.m.