Triple

T30914718
Position Surface form Disambiguated ID Type / Status
Subject Correale family E787545 entity
Predicate category P87 FINISHED
Object History of Sorrento
The History of Sorrento encompasses the cultural, political, and social development of the coastal Italian town of Sorrento from antiquity to the modern era.
E1939118 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: History of Sorrento | Statement: [Correale family, category, History of Sorrento]
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: History of Sorrento
Triple: [Correale family, category, History of Sorrento]
Generated description
The History of Sorrento encompasses the cultural, political, and social development of the coastal Italian town of Sorrento from antiquity to the modern era.

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_69f224be300c8190a6513ce1ee0a7026 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6928720ec8190992ea663647ca819 completed May 3, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28e464082c81908b42a5fcc30e1f06 completed June 10, 2026, 4:13 a.m.
NEDg Description generation batch_6a28e8a299908190a16f145e901f8edd completed June 10, 2026, 4:31 a.m.
NED2 Entity disambiguation (via description) batch_6a28e91bbbcc8190bf420aaed9cf4b8a completed June 10, 2026, 4:33 a.m.
Created at: April 29, 2026, 8:51 p.m.