Triple

T33230846
Position Surface form Disambiguated ID Type / Status
Subject caponata E850687 entity
Predicate isPartOfCuisine P70749 FINISHED
Object Sicilian cuisine
Sicilian cuisine is a regional Italian culinary tradition known for its rich blend of Mediterranean flavors, featuring abundant seafood, vegetables, olive oil, and influences from Greek, Arab, and Spanish cooking.
E2041214 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: Sicilian cuisine | Statement: [caponata, isPartOfCuisine, Sicilian cuisine]
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: Sicilian cuisine
Triple: [caponata, isPartOfCuisine, Sicilian cuisine]
Generated description
Sicilian cuisine is a regional Italian culinary tradition known for its rich blend of Mediterranean flavors, featuring abundant seafood, vegetables, olive oil, and influences from Greek, Arab, and Spanish cooking.

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_69f349613f988190a1eb75467d167122 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6daad1ab48190a98b4cb35f4a202d completed May 3, 2026, 5:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a352fdc8c148190842489e10e5f1076 completed June 19, 2026, 12:02 p.m.
NEDg Description generation batch_6a3530dd26188190990588834837e034 completed June 19, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_6a3531f1f7b8819095b3ebb58ff09aa7 completed June 19, 2026, 12:11 p.m.
Created at: May 1, 2026, 1:30 a.m.