Triple

T37428126
Position Surface form Disambiguated ID Type / Status
Subject Principality of Ansbach-Bayreuth E930050 entity
Predicate partOf P40 FINISHED
Object Prussian Franconia
Prussian Franconia was a group of former Franconian principalities in southern Germany that came under the control of the Kingdom of Prussia in the late 18th century.
E2228954 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: Prussian Franconia | Statement: [Principality of Ansbach-Bayreuth, partOf, Prussian Franconia]
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: Prussian Franconia
Triple: [Principality of Ansbach-Bayreuth, partOf, Prussian Franconia]
Generated description
Prussian Franconia was a group of former Franconian principalities in southern Germany that came under the control of the Kingdom of Prussia in the late 18th 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_69f76ebf0f288190ba198a78341613b8 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb8db0665c8190b697abf7ff6deb22 completed May 6, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a408c28494881909f4ced5fb1be4f3b completed June 28, 2026, 2:51 a.m.
NEDg Description generation batch_6a408cfaa42c8190955793445f4f2eab completed June 28, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_6a408dd999148190ab3069df803162ff completed June 28, 2026, 2:58 a.m.
Created at: May 3, 2026, 4:16 p.m.