Triple

T31372198
Position Surface form Disambiguated ID Type / Status
Subject Schauspiel Frankfurt E800192 entity
Predicate hasArtisticDirector P255 FINISHED
Object Anselm Weber
Anselm Weber is a German theater director and manager known for leading major German-speaking stages, including serving as artistic director of Schauspiel Frankfurt.
E2295302 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: Anselm Weber | Statement: [Schauspiel Frankfurt, hasArtisticDirector, Anselm Weber]
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: Anselm Weber
Triple: [Schauspiel Frankfurt, hasArtisticDirector, Anselm Weber]
Generated description
Anselm Weber is a German theater director and manager known for leading major German-speaking stages, including serving as artistic director of Schauspiel Frankfurt.

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_69f224e6b7448190ac6bf97ad7364160 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69f8a5d2c81908d4d0d43fc72966f completed May 3, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7d37a7306c81908efc25d41e669f37 completed Aug. 13, 2026, 3:19 a.m.
NEDg Description generation batch_6a7d38503c108190b604851e434212bd completed Aug. 13, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_6a7d38a656e8819092d88a557dfaf167 completed Aug. 13, 2026, 3:23 a.m.
Created at: April 29, 2026, 9:18 p.m.