Triple

T24437775
Position Surface form Disambiguated ID Type / Status
Subject Erwin Piscator E616170 entity
Predicate spouse P13 FINISHED
Object Maria Ley Piscator
Maria Ley Piscator was an Austrian-born writer, actress, and influential theater director and educator, known for her collaboration with and marriage to pioneering political theater director Erwin Piscator.
E1639441 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: Maria Ley Piscator | Statement: [Erwin Piscator, spouse, Maria Ley Piscator]
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: Maria Ley Piscator
Triple: [Erwin Piscator, spouse, Maria Ley Piscator]
Generated description
Maria Ley Piscator was an Austrian-born writer, actress, and influential theater director and educator, known for her collaboration with and marriage to pioneering political theater director Erwin Piscator.

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_69e2d7ec44b081909ccaf1f3bbec0641 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f297881fa08190b82bdc5ebeae96f7 completed April 29, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee6d49f08190b52aba10dd725568 completed May 22, 2026, 5:49 a.m.
NEDg Description generation batch_6a0fef9b5d0081909c38c3b72b0d0304 completed May 22, 2026, 5:54 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff0cc90508190b5d68bedeb4531aa completed May 22, 2026, 5:59 a.m.
Created at: April 18, 2026, 2:16 a.m.