Triple

T27316692
Position Surface form Disambiguated ID Type / Status
Subject Ernst Heinrich of Saxony E689367 entity
Predicate givenName P17 FINISHED
Object Ernst Heinrich
Ernst Heinrich was a 20th-century German prince of the House of Wettin, known as the last Crown Prince of Saxony before the abolition of the monarchy after World War I.
E1940641 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: Ernst Heinrich | Statement: [Ernst Heinrich of Saxony, givenName, Ernst Heinrich]
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: Ernst Heinrich
Triple: [Ernst Heinrich of Saxony, givenName, Ernst Heinrich]
Generated description
Ernst Heinrich was a 20th-century German prince of the House of Wettin, known as the last Crown Prince of Saxony before the abolition of the monarchy after World War I.

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_69ef355c53a08190a8a92e355a7ce115 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f627b69d0881908e5da0d2d6acedae completed May 2, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28fb843dc88190bc6b421c9ed6fde1 completed June 10, 2026, 5:52 a.m.
NEDg Description generation batch_6a28ffc3037481909e380c0b60ebce5c completed June 10, 2026, 6:10 a.m.
NED2 Entity disambiguation (via description) batch_6a29005bb6bc81909fa20caeb92ac2be completed June 10, 2026, 6:12 a.m.
Created at: April 27, 2026, 11:31 a.m.