Triple

T31195351
Position Surface form Disambiguated ID Type / Status
Subject Princess Joséphine Caroline of Belgium E795303 entity
Predicate child P120 FINISHED
Object Prince Albrecht of Hohenzollern
Prince Albrecht of Hohenzollern was a German nobleman and member of the Hohenzollern-Sigmaringen dynasty, notable for his ties to both German and Belgian royal families.
E2042758 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: Prince Albrecht of Hohenzollern | Statement: [Princess Joséphine Caroline of Belgium, child, Prince Albrecht of Hohenzollern]
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: Prince Albrecht of Hohenzollern
Triple: [Princess Joséphine Caroline of Belgium, child, Prince Albrecht of Hohenzollern]
Generated description
Prince Albrecht of Hohenzollern was a German nobleman and member of the Hohenzollern-Sigmaringen dynasty, notable for his ties to both German and Belgian royal families.

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_69f224d7a6a481908187c4362a8a525f completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69bbe12f48190b60052af284c1d27 completed May 3, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3538e906648190955ebab34618bda7 completed June 19, 2026, 12:41 p.m.
NEDg Description generation batch_6a3539a67a2481908c1ce778bc0a7cd4 completed June 19, 2026, 12:44 p.m.
NED2 Entity disambiguation (via description) batch_6a353a2156248190b503b83c3689e5de completed June 19, 2026, 12:46 p.m.
Created at: April 29, 2026, 9:09 p.m.