Triple

T26757988
Position Surface form Disambiguated ID Type / Status
Subject Exilliteratur E674724 entity
Predicate wichtigeAutoren P12787 FINISHED
Object Friedrich Torberg
Friedrich Torberg was an Austrian-Jewish writer, journalist, and satirist best known for his anti-fascist exile literature and his novel "Der Schüler Gerber."
E2289951 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: Friedrich Torberg | Statement: [Exilliteratur, wichtigeAutoren, Friedrich Torberg]
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: Friedrich Torberg
Triple: [Exilliteratur, wichtigeAutoren, Friedrich Torberg]
Generated description
Friedrich Torberg was an Austrian-Jewish writer, journalist, and satirist best known for his anti-fascist exile literature and his novel "Der Schüler Gerber."

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_69eecda6e9dc81908452fab3ba17ed9b completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f64cb2b5f4819092e363d5076cddbb completed May 2, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5b816e95cc81909280d4b75e29c7f6 completed July 18, 2026, 1:36 p.m.
NEDg Description generation batch_6a5b81bb1194819095bdf97b108ec9cb completed July 18, 2026, 1:38 p.m.
NED2 Entity disambiguation (via description) batch_6a5b828870c08190b90ead832ba0835e completed July 18, 2026, 1:41 p.m.
Created at: April 27, 2026, 3:56 a.m.