Triple

T33177347
Position Surface form Disambiguated ID Type / Status
Subject Thomas Tuschl E849217 entity
Predicate hasAcademicAdvisor P167 FINISHED
Object Ernst-Ludwig Winnacker
Ernst-Ludwig Winnacker is a German biochemist and research administrator known for his contributions to molecular biology and for leading major scientific organizations such as the Deutsche Forschungsgemeinschaft (DFG) and the European Research Council (ERC).
E2039745 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: Ernst-Ludwig Winnacker | Statement: [Thomas Tuschl, hasAcademicAdvisor, Ernst-Ludwig Winnacker]
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: Ernst-Ludwig Winnacker
Triple: [Thomas Tuschl, hasAcademicAdvisor, Ernst-Ludwig Winnacker]
Generated description
Ernst-Ludwig Winnacker is a German biochemist and research administrator known for his contributions to molecular biology and for leading major scientific organizations such as the Deutsche Forschungsgemeinschaft (DFG) and the European Research Council (ERC).

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_69f3495d06508190b0b7729982982cea completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d9913a048190b3d5241867664331 completed May 3, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3525ca2a8481909c95971cd1d35603 completed June 19, 2026, 11:19 a.m.
NEDg Description generation batch_6a3526724b348190b30a37434afbee97 completed June 19, 2026, 11:22 a.m.
NED2 Entity disambiguation (via description) batch_6a35279eb8b08190970ba8ea52ac75a2 completed June 19, 2026, 11:27 a.m.
Created at: May 1, 2026, 1:29 a.m.