Triple

T26919926
Position Surface form Disambiguated ID Type / Status
Subject Trieste metropolitan area E677615 entity
Predicate hasPart P35 FINISHED
Object Villa Opicina
Villa Opicina is a town and suburb of Trieste in northeastern Italy, known for its position near the Slovenian border and its historic tramway connection to Trieste.
E1749503 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: Villa Opicina | Statement: [Trieste metropolitan area, hasPart, Villa Opicina]
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: Villa Opicina
Triple: [Trieste metropolitan area, hasPart, Villa Opicina]
Generated description
Villa Opicina is a town and suburb of Trieste in northeastern Italy, known for its position near the Slovenian border and its historic tramway connection to Trieste.

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_69eee9bdebc48190ba90a12a63e09c73 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f6200cee788190ba32d1379b50ba57 completed May 2, 2026, 4:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a122993c3fc81909abb8b1a255ecedf completed May 23, 2026, 10:26 p.m.
NEDg Description generation batch_6a122a2048408190a3a8cf5a2efa9b08 completed May 23, 2026, 10:28 p.m.
NED2 Entity disambiguation (via description) batch_6a122ac1713481909a80761bb471ef49 completed May 23, 2026, 10:31 p.m.
Created at: April 27, 2026, 6:06 a.m.