Triple

T25175743
Position Surface form Disambiguated ID Type / Status
Subject Princess Leonore d’Este E630440 entity
Predicate originalLanguageName P15 FINISHED
Object Leonore d’Este
Leonore d’Este was a Renaissance Italian noblewoman of the influential House of Este, known primarily as the daughter of Duke Ercole I d’Este of Ferrara.
E1677830 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: Leonore d’Este | Statement: [Princess Leonore d’Este, originalLanguageName, Leonore d’Este]
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: Leonore d’Este
Triple: [Princess Leonore d’Este, originalLanguageName, Leonore d’Este]
Generated description
Leonore d’Este was a Renaissance Italian noblewoman of the influential House of Este, known primarily as the daughter of Duke Ercole I d’Este of Ferrara.

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_69e75a88fdf081908e47ae6e195c14e1 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46dc040088190958bb7a6633fd016 completed May 1, 2026, 9:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1075c5b7cc8190b2c9c6fea539fd28 completed May 22, 2026, 3:27 p.m.
NEDg Description generation batch_6a1079a631c88190b31f8fff309f9c00 completed May 22, 2026, 3:43 p.m.
NED2 Entity disambiguation (via description) batch_6a107a64b13081908a7364097a65067a completed May 22, 2026, 3:46 p.m.
Created at: April 21, 2026, 12:34 p.m.