Triple

T27861559
Position Surface form Disambiguated ID Type / Status
Subject Knud, Hereditary Prince of Denmark E704242 entity
Predicate fullName P16 FINISHED
Object Knud Christian Frederik
Knud Christian Frederik was a Danish prince who served as Hereditary Prince of Denmark and was the younger brother of King Frederick IX.
E1847794 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: Knud Christian Frederik | Statement: [Knud, Hereditary Prince of Denmark, fullName, Knud Christian Frederik]
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: Knud Christian Frederik
Triple: [Knud, Hereditary Prince of Denmark, fullName, Knud Christian Frederik]
Generated description
Knud Christian Frederik was a Danish prince who served as Hereditary Prince of Denmark and was the younger brother of King Frederick IX.

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_69ef840f12408190b539d00d79658abf completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f639438ce88190a72ea1695afc5794 completed May 2, 2026, 5:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a251f4220448190920ea22955f0dba0 completed June 7, 2026, 7:35 a.m.
NEDg Description generation batch_6a25242352f08190805e663c6bb680cc completed June 7, 2026, 7:56 a.m.
NED2 Entity disambiguation (via description) batch_6a2527e117c88190989c7965f5d99f87 completed June 7, 2026, 8:12 a.m.
Created at: April 27, 2026, 6:18 p.m.