Triple

T36607923
Position Surface form Disambiguated ID Type / Status
Subject Nuclear-Free Future Award E903087 entity
Predicate founder P104 FINISHED
Object Klaus Renoldner
Klaus Renoldner is an Austrian physician and environmental activist best known for his leadership in the anti-nuclear movement and his role in establishing the Nuclear-Free Future Award.
E2295896 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: Klaus Renoldner | Statement: [Nuclear-Free Future Award, founder, Klaus Renoldner]
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: Klaus Renoldner
Triple: [Nuclear-Free Future Award, founder, Klaus Renoldner]
Generated description
Klaus Renoldner is an Austrian physician and environmental activist best known for his leadership in the anti-nuclear movement and his role in establishing the Nuclear-Free Future Award.

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_69f76e66b7b88190848f7a3e1188915f completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c341dab881908f03317762fa9e5d completed May 3, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a820a403f80819084e284bf2274003c completed Aug. 16, 2026, 7:06 p.m.
NEDg Description generation batch_6a820aa459408190b363bcd884835aa7 completed Aug. 16, 2026, 7:08 p.m.
NED2 Entity disambiguation (via description) batch_6a820b00bcb481908abd93bfd1b75f06 completed Aug. 16, 2026, 7:09 p.m.
Created at: May 3, 2026, 4:11 p.m.