Triple

T17377409
Position Surface form Disambiguated ID Type / Status
Subject Albert the Bear E422475 entity
Predicate mother P120 FINISHED
Object Eilika of Saxony
Eilika of Saxony was a German noblewoman of the Billung dynasty, notable as the wife of Otto of Ballenstedt and mother of Albert the Bear, the first Margrave of Brandenburg.
E1877601 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: Eilika of Saxony | Statement: [Albert the Bear, mother, Eilika of Saxony]
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: Eilika of Saxony
Triple: [Albert the Bear, mother, Eilika of Saxony]
Generated description
Eilika of Saxony was a German noblewoman of the Billung dynasty, notable as the wife of Otto of Ballenstedt and mother of Albert the Bear, the first Margrave of Brandenburg.

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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a6ea56c8190b56d966ccf2c91f7 completed April 19, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a266138156c8190829cc1164b7c86c9 completed June 8, 2026, 6:29 a.m.
NEDg Description generation batch_6a26658b86e88190b68b3a7d183a72e9 completed June 8, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_6a266c326a7081909d55ff20b5c3b851 completed June 8, 2026, 7:16 a.m.
Created at: April 10, 2026, 5:45 a.m.