Triple

T36396201
Position Surface form Disambiguated ID Type / Status
Subject Jardins de Pedralbes E896486 entity
Predicate hasAccess P273 FINISHED
Object Carrer de Jordi Girona
Carrer de Jordi Girona is a street in Barcelona’s Les Corts district, known for serving the university and research campus area near the Pedralbes neighborhood.
E2253144 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: Carrer de Jordi Girona | Statement: [Jardins de Pedralbes, hasAccess, Carrer de Jordi Girona]
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: Carrer de Jordi Girona
Triple: [Jardins de Pedralbes, hasAccess, Carrer de Jordi Girona]
Generated description
Carrer de Jordi Girona is a street in Barcelona’s Les Corts district, known for serving the university and research campus area near the Pedralbes neighborhood.

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_69f76e52e3108190becf70b090ae7bd6 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd11938c81908ac7da5e5095cff5 completed May 3, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a415416b87c8190b363c36cfb65380c completed June 28, 2026, 5:04 p.m.
NEDg Description generation batch_6a4154e5fdc08190bd4f569fadefb974 completed June 28, 2026, 5:07 p.m.
NED2 Entity disambiguation (via description) batch_6a41555e490c8190bdb21d39474e218e completed June 28, 2026, 5:09 p.m.
Created at: May 3, 2026, 4:10 p.m.