Triple

T24812916
Position Surface form Disambiguated ID Type / Status
Subject La donna del lago E620837 entity
Predicate librettist P1141 FINISHED
Object Andrea Leone Tottola
Andrea Leone Tottola was a 19th-century Italian librettist best known for writing texts for operas by composers such as Gioachino Rossini and Gaetano Donizetti.
E1667340 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: Andrea Leone Tottola | Statement: [La donna del lago, librettist, Andrea Leone Tottola]
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: Andrea Leone Tottola
Triple: [La donna del lago, librettist, Andrea Leone Tottola]
Generated description
Andrea Leone Tottola was a 19th-century Italian librettist best known for writing texts for operas by composers such as Gioachino Rossini and Gaetano Donizetti.

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_69e2fabfd4648190bd0e5c7f4dbb6cab completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4220c07dc81909878ee802bb2e8d0 completed May 1, 2026, 3:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105ccbe3508190813da59d5f373dc1 completed May 22, 2026, 1:40 p.m.
NEDg Description generation batch_6a105df4d07881909cb98f27deeb0adb completed May 22, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_6a105ef626c08190933088d575b2e923 completed May 22, 2026, 1:49 p.m.
Created at: April 18, 2026, 4:55 a.m.