Triple

T17402149
Position Surface form Disambiguated ID Type / Status
Subject Charles Frederick, Grand Duke of Baden E423116 entity
Predicate mother P120 FINISHED
Object Amalia of Nassau-Dietz
Amalia of Nassau-Dietz was an 18th-century Dutch princess of the House of Orange-Nassau who became a prominent German duchess through her marriage into the Baden ruling family.
E1883862 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: Amalia of Nassau-Dietz | Statement: [Charles Frederick, Grand Duke of Baden, mother, Amalia of Nassau-Dietz]
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: Amalia of Nassau-Dietz
Triple: [Charles Frederick, Grand Duke of Baden, mother, Amalia of Nassau-Dietz]
Generated description
Amalia of Nassau-Dietz was an 18th-century Dutch princess of the House of Orange-Nassau who became a prominent German duchess through her marriage into the Baden ruling family.

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_69d889d710288190bf0f4762801fefae completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43b046ad88190a95bbeda4e602514 completed April 19, 2026, 2:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a26c8bf0828819087666607bdca4ab8 completed June 8, 2026, 1:50 p.m.
NEDg Description generation batch_6a26cd2db9bc8190bdbe700f6522ef39 completed June 8, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_6a26d94836a88190bf71dbdf15a26d71 completed June 8, 2026, 3:01 p.m.
Created at: April 10, 2026, 5:45 a.m.