Triple

T26789819
Position Surface form Disambiguated ID Type / Status
Subject Gustav Körner E670484 entity
Predicate alternateName P39 FINISHED
Object Gustave Koerner
Gustave Koerner was a 19th-century German-American politician, jurist, and abolitionist who served as Lieutenant Governor of Illinois and was an influential figure in the early Republican Party.
E1885588 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: Gustave Koerner | Statement: [Gustav Körner, alternateName, Gustave Koerner]
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: Gustave Koerner
Triple: [Gustav Körner, alternateName, Gustave Koerner]
Generated description
Gustave Koerner was a 19th-century German-American politician, jurist, and abolitionist who served as Lieutenant Governor of Illinois and was an influential figure in the early Republican Party.

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_69eeb31d45f8819089f52ebdbc556218 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f619baac9c8190afeb5089b347e74b completed May 2, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26e5c7324481908d7727a6d2b54002 completed June 8, 2026, 3:54 p.m.
NEDg Description generation batch_6a26e6776f9481908df0bc905c664756 completed June 8, 2026, 3:57 p.m.
NED2 Entity disambiguation (via description) batch_6a26e7abb57c819095ad0e1dbf8a9be8 completed June 8, 2026, 4:02 p.m.
Created at: April 27, 2026, 4:15 a.m.