Triple

T36607946
Position Surface form Disambiguated ID Type / Status
Subject Nuclear-Free Future Award E903087 entity
Predicate notableRecipient P108 FINISHED
Object Hans-Peter Dürr
Hans-Peter Dürr was a German physicist and peace activist known for his work in quantum physics and his advocacy for nuclear disarmament and environmental protection.
E2295905 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: Hans-Peter Dürr | Statement: [Nuclear-Free Future Award, notableRecipient, Hans-Peter Dürr]
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: Hans-Peter Dürr
Triple: [Nuclear-Free Future Award, notableRecipient, Hans-Peter Dürr]
Generated description
Hans-Peter Dürr was a German physicist and peace activist known for his work in quantum physics and his advocacy for nuclear disarmament and environmental protection.

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_6a820bdc9238819089be4d53a64773b5 completed Aug. 16, 2026, 7:13 p.m.
NEDg Description generation batch_6a820c42e128819084c3cc3d4080245c completed Aug. 16, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_6a820c8446888190a588cf15e8ffc718 completed Aug. 16, 2026, 7:16 p.m.
Created at: May 3, 2026, 4:11 p.m.