Triple

T34588554
Position Surface form Disambiguated ID Type / Status
Subject Baron Klaus Wulfenbach E888112 entity
Predicate fullName P16 FINISHED
Object Klaus Wulfenbach
Klaus Wulfenbach is a powerful and feared "spark" (mad scientist) and baron who serves as a major political and military leader in the steampunk webcomic *Girl Genius*.
E2294726 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 Wulfenbach | Statement: [Baron Klaus Wulfenbach, fullName, Klaus Wulfenbach]
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 Wulfenbach
Triple: [Baron Klaus Wulfenbach, fullName, Klaus Wulfenbach]
Generated description
Klaus Wulfenbach is a powerful and feared "spark" (mad scientist) and baron who serves as a major political and military leader in the steampunk webcomic *Girl Genius*.

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_69f349d3bfcc81909874c99e646fb3ea completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f720c9eb9c819082e5137cd7fbdbf4 completed May 3, 2026, 10:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7c13a60e3881909f7a9e2f1b9fe3ca completed Aug. 12, 2026, 6:33 a.m.
NEDg Description generation batch_6a7c14160a8c8190a1a4c9f46ed84775 completed Aug. 12, 2026, 6:35 a.m.
NED2 Entity disambiguation (via description) batch_6a7c1476f4148190b6a3a1beff5daaa3 completed Aug. 12, 2026, 6:36 a.m.
Created at: May 1, 2026, 2:03 a.m.