Triple

T30830706
Position Surface form Disambiguated ID Type / Status
Subject Ponte San Pietro E785207 entity
Predicate partOf P40 FINISHED
Object Bergamo metropolitan area
The Bergamo metropolitan area is an urban and suburban agglomeration in Lombardy, northern Italy, centered on the city of Bergamo and encompassing its surrounding municipalities.
E1935403 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: Bergamo metropolitan area | Statement: [Ponte San Pietro, partOf, Bergamo metropolitan area]
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: Bergamo metropolitan area
Triple: [Ponte San Pietro, partOf, Bergamo metropolitan area]
Generated description
The Bergamo metropolitan area is an urban and suburban agglomeration in Lombardy, northern Italy, centered on the city of Bergamo and encompassing its surrounding municipalities.

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_69f224b6642481909e8d701de2cd1a53 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f690f9b8ac8190b5913fffaae48346 completed May 3, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28c7c7e7708190b00ce1eb12ee4b64 completed June 10, 2026, 2:11 a.m.
NEDg Description generation batch_6a28cb4d5ccc8190a7884dca165b6d73 completed June 10, 2026, 2:26 a.m.
NED2 Entity disambiguation (via description) batch_6a28cc288a7481909e44d08fd4de3e0b completed June 10, 2026, 2:30 a.m.
Created at: April 29, 2026, 8:44 p.m.