Triple

T30459412
Position Surface form Disambiguated ID Type / Status
Subject Christian Griepenkerl E774953 entity
Predicate notableStudent P4838 FINISHED
Object Franz Matsch
Franz Matsch was an Austrian painter and sculptor associated with the Vienna Secession, known for his decorative and monumental works created alongside Gustav Klimt and Ernst Klimt.
E1964018 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: Franz Matsch | Statement: [Christian Griepenkerl, notableStudent, Franz Matsch]
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: Franz Matsch
Triple: [Christian Griepenkerl, notableStudent, Franz Matsch]
Generated description
Franz Matsch was an Austrian painter and sculptor associated with the Vienna Secession, known for his decorative and monumental works created alongside Gustav Klimt and Ernst Klimt.

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_69f22494fb60819095d893de0284f886 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f686ef5ebc819081199a38f7d58adc completed May 2, 2026, 11:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2b142fa74c819094e0c77272ce0e60 completed June 11, 2026, 8:01 p.m.
NEDg Description generation batch_6a2b14e482108190a30e55461ea4478f completed June 11, 2026, 8:04 p.m.
NED2 Entity disambiguation (via description) batch_6a2b15c455f88190b2e64d5e21982529 completed June 11, 2026, 8:08 p.m.
Created at: April 29, 2026, 8:10 p.m.