Triple

T28332196
Position Surface form Disambiguated ID Type / Status
Subject L’italiana in Algeri E717565 entity
Predicate librettist P1141 FINISHED
Object Angelo Anelli
Angelo Anelli was an Italian librettist and writer of the late 18th and early 19th centuries, best known for providing texts for comic operas by composers such as Rossini.
E1982443 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: Angelo Anelli | Statement: [L’italiana in Algeri, librettist, Angelo Anelli]
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: Angelo Anelli
Triple: [L’italiana in Algeri, librettist, Angelo Anelli]
Generated description
Angelo Anelli was an Italian librettist and writer of the late 18th and early 19th centuries, best known for providing texts for comic operas by composers such as Rossini.

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_69eff6e9a57c8190a69c2c74b5d72119 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64bcec4748190b71a5c9e9a66d843 completed May 2, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2e7fb2a27081909d14476e87263821 completed June 14, 2026, 10:17 a.m.
NEDg Description generation batch_6a2e80bfc09c81908b0f21d5dc3629e9 completed June 14, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_6a2e81c63b8081909989e5e18ce19954 completed June 14, 2026, 10:26 a.m.
Created at: April 28, 2026, 12:33 a.m.