Triple

T26169661
Position Surface form Disambiguated ID Type / Status
Subject Catharina of Württemberg E654363 entity
Predicate spouseOccupation P4765 FINISHED
Object King of Westphalia
The King of Westphalia was the monarch of the short-lived Napoleonic client kingdom of Westphalia, established in 1807 in parts of modern-day Germany and ruled by Jérôme Bonaparte.
E58019 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: King of Westphalia | Statement: [Catharina of Württemberg, spouseOccupation, King of Westphalia]
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: King of Westphalia
Triple: [Catharina of Württemberg, spouseOccupation, King of Westphalia]
Generated description
The King of Westphalia was the monarch of the short-lived Napoleonic client kingdom of Westphalia, established in 1807 in parts of modern-day Germany and ruled by Jérôme Bonaparte.

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_69ee5b44391c81908bdbd8813ba9aa99 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60c425de88190a221b40e81d0dcc1 completed May 2, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11277963648190b63c6eae76562fd3 completed May 23, 2026, 4:05 a.m.
NEDg Description generation batch_6a112d6278448190b2d341a940b350cd completed May 23, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_6a112f429b708190a0b849fc00ec4b51 completed May 23, 2026, 4:38 a.m.
Created at: April 26, 2026, 8:34 p.m.