Triple

T28128952
Position Surface form Disambiguated ID Type / Status
Subject Margaret of Austria E711007 entity
Predicate alsoKnownAs P39 FINISHED
Object Marguerite d’Autriche
Marguerite d’Autriche, or Margaret of Austria, was a Habsburg archduchess and influential regent of the Low Countries in the early 16th century, known for her political acumen and patronage of Renaissance culture.
E1977203 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: Marguerite d’Autriche | Statement: [Margaret of Austria, alsoKnownAs, Marguerite d’Autriche]
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: Marguerite d’Autriche
Triple: [Margaret of Austria, alsoKnownAs, Marguerite d’Autriche]
Generated description
Marguerite d’Autriche, or Margaret of Austria, was a Habsburg archduchess and influential regent of the Low Countries in the early 16th century, known for her political acumen and patronage of Renaissance culture.

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_69ef9b73bd288190a21ae3d6aa14f386 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f640ff720c8190a6edb7f6b5dd5b7e completed May 2, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2d9d269fc88190b07fe448a88a726e completed June 13, 2026, 6:10 p.m.
NEDg Description generation batch_6a2d9e2593f4819092c89187e84af3c9 completed June 13, 2026, 6:15 p.m.
NED2 Entity disambiguation (via description) batch_6a2d9f083f0481909184bb37c1ce0e7a completed June 13, 2026, 6:18 p.m.
Created at: April 27, 2026, 9:21 p.m.