Triple

T32442190
Position Surface form Disambiguated ID Type / Status
Subject Montilivi neighborhood E829044 entity
Predicate hasTransportConnection P845 FINISHED
Object Girona urban bus network
The Girona urban bus network is the city’s public transportation system, operating multiple routes that connect Girona’s neighborhoods and key destinations.
E2005795 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: Girona urban bus network | Statement: [Montilivi neighborhood, hasTransportConnection, Girona urban bus network]
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: Girona urban bus network
Triple: [Montilivi neighborhood, hasTransportConnection, Girona urban bus network]
Generated description
The Girona urban bus network is the city’s public transportation system, operating multiple routes that connect Girona’s neighborhoods and key destinations.

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_69f3491d2e5c819092b1c9535beff8ec completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c2e310788190b57a9adbda4dd895 completed May 3, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a344f3658708190b9c31ca163117f19 completed June 18, 2026, 8:04 p.m.
NEDg Description generation batch_6a3453206fb081908b641a4a804eb814 completed June 18, 2026, 8:20 p.m.
NED2 Entity disambiguation (via description) batch_6a34538c05708190a42d883a62a92893 completed June 18, 2026, 8:22 p.m.
Created at: May 1, 2026, 12:55 a.m.