Triple

T24762956
Position Surface form Disambiguated ID Type / Status
Subject Appiani family E619499 entity
Predicate member P10 FINISHED
Object Jacopo III Appiani
Jacopo III Appiani was a 16th-century Italian nobleman who ruled the small but strategically important principality of Piombino as a member of the Appiani dynasty.
E1662693 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: Jacopo III Appiani | Statement: [Appiani family, member, Jacopo III Appiani]
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: Jacopo III Appiani
Triple: [Appiani family, member, Jacopo III Appiani]
Generated description
Jacopo III Appiani was a 16th-century Italian nobleman who ruled the small but strategically important principality of Piombino as a member of the Appiani dynasty.

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_69e2fabbea94819092ed41348909622f completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f410a330f0819081bc60b9275d883d completed May 1, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a104882d9e88190afc2212fb54d0b73 completed May 22, 2026, 12:13 p.m.
NEDg Description generation batch_6a10496ad0748190b797fea89fc9472d completed May 22, 2026, 12:17 p.m.
NED2 Entity disambiguation (via description) batch_6a104bbb9b6c81908fcc21c8c027b9de completed May 22, 2026, 12:27 p.m.
Created at: April 18, 2026, 4:27 a.m.