Triple

T19795486
Position Surface form Disambiguated ID Type / Status
Subject Trial of Marie Antoinette E475528 entity
Predicate hasNotableQuote P492 FINISHED
Object "I was a queen, and you took away my crown; a wife, and you killed my husband; a mother, and you deprived me of my children" (attributed) LITERAL FINISHED

How this triple was built (1 step)

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: "I was a queen, and you took away my crown; a wife, and you killed my husband; a mother, and you deprived me of my children" (attributed) | Statement: [Trial of Marie Antoinette, hasNotableQuote, "I was a queen, and you took away my crown; a wife, and you killed my husband; a mother, and you deprived me of my children" (attributed)]

Provenance (2 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_69d8e51b014081908b263e167370529a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e653c659088190928fa4c9264135d3 completed April 20, 2026, 4:26 p.m.
Created at: April 10, 2026, 1:49 p.m.