Triple

T34873820
Position Surface form Disambiguated ID Type / Status
Subject William Wrede E1005823 entity
Predicate familyName P18 FINISHED
Object Wrede
Wrede is a German surname most notably associated with William Wrede, a pioneering New Testament scholar of the early 20th century.
E1708616 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: Wrede | Statement: [William Wrede, familyName, Wrede]
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: Wrede
Triple: [William Wrede, familyName, Wrede]
Generated description
Wrede is a German surname most notably associated with William Wrede, a pioneering New Testament scholar of the early 20th century.

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_69f76dbde1c08190a24e7f9beb564c8d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7819a187481909b9248423be51635 completed May 3, 2026, 5:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37796692bc8190bc424b312fd450f6 completed June 21, 2026, 5:40 a.m.
NEDg Description generation batch_6a377a42a0608190afd382cdf88144e5 completed June 21, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_6a377ad9766c8190ac3a89dd73c5754c completed June 21, 2026, 5:47 a.m.
Created at: May 3, 2026, 4 p.m.