Triple

T35487383
Position Surface form Disambiguated ID Type / Status
Subject Castelvetro di Modena E1025633 entity
Predicate hasPart P35 FINISHED
Object Osteriola
Osteriola is a small locality or hamlet within the municipality of Castelvetro di Modena in the Emilia-Romagna region of northern Italy.
E2145523 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: Osteriola | Statement: [Castelvetro di Modena, hasPart, Osteriola]
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: Osteriola
Triple: [Castelvetro di Modena, hasPart, Osteriola]
Generated description
Osteriola is a small locality or hamlet within the municipality of Castelvetro di Modena in the Emilia-Romagna region of northern Italy.

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_6a3852dfe5d881909ad98fe0fde1741e completed June 21, 2026, 9:08 p.m.
NEDg Description generation batch_6a38545a48a881909970b888d152b021 completed June 21, 2026, 9:15 p.m.
NED2 Entity disambiguation (via description) batch_6a3854ee0cc08190a542392edeedb715 completed June 21, 2026, 9:17 p.m.
Created at: May 3, 2026, 4:04 p.m.