Triple

T15159705
Position Surface form Disambiguated ID Type / Status
Subject Alessandro Pavolini E362174 entity
Predicate sibling P363 FINISHED
Object Corrado Pavolini
Corrado Pavolini was an Italian writer, journalist, and screenwriter active in the early to mid-20th century.
E1592482 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: Corrado Pavolini | Statement: [Alessandro Pavolini, sibling, Corrado Pavolini]
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: Corrado Pavolini
Triple: [Alessandro Pavolini, sibling, Corrado Pavolini]
Generated description
Corrado Pavolini was an Italian writer, journalist, and screenwriter active in the early to mid-20th century.

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_69d85a087b7c81908baa94a53dac8d68 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0060dd71881908ecc4a4f52d438a5 completed April 15, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0f4531481c81908b3c1e81d1322994 completed May 21, 2026, 5:47 p.m.
NEDg Description generation batch_6a0f46b69d288190b3fb6dcea9fb44b5 completed May 21, 2026, 5:53 p.m.
NED2 Entity disambiguation (via description) batch_6a0f476e8eb88190a895453552c92b9a completed May 21, 2026, 5:57 p.m.
Created at: April 10, 2026, 3:08 a.m.