Triple

T35487342
Position Surface form Disambiguated ID Type / Status
Subject Bomporto E1025632 entity
Predicate hasSubdivision P747 FINISHED
Object Sorbara
Sorbara is a frazione (hamlet) in the Emilia-Romagna region of northern Italy, known especially for producing Lambrusco di Sorbara wine.
E2294893 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: Sorbara | Statement: [Bomporto, hasSubdivision, Sorbara]
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: Sorbara
Triple: [Bomporto, hasSubdivision, Sorbara]
Generated description
Sorbara is a frazione (hamlet) in the Emilia-Romagna region of northern Italy, known especially for producing Lambrusco di Sorbara wine.

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_69f76dfbcdd881908c7b0b6bc502252b completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f796f1743c819088938812cbad7385 completed May 3, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7c2ed1f6c481908ecf6ef34d98b44c completed Aug. 12, 2026, 8:29 a.m.
NEDg Description generation batch_6a7c31bef6fc8190861b0d62ff7d96a7 completed Aug. 12, 2026, 8:41 a.m.
NED2 Entity disambiguation (via description) batch_6a7c3b60d9b0819086e498337f1225c8 completed Aug. 12, 2026, 9:22 a.m.
Created at: May 3, 2026, 4:04 p.m.