Triple

T34467640
Position Surface form Disambiguated ID Type / Status
Subject Entença E884815 entity
Predicate neighbourhood P988 FINISHED
Object La Nova Esquerra de l'Eixample
La Nova Esquerra de l'Eixample is a residential neighborhood in Barcelona’s Eixample district, known for its grid-pattern streets, mixed modernist and contemporary architecture, and vibrant local commerce.
E2096861 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: La Nova Esquerra de l'Eixample | Statement: [Entença, neighbourhood, La Nova Esquerra de l'Eixample]
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: La Nova Esquerra de l'Eixample
Triple: [Entença, neighbourhood, La Nova Esquerra de l'Eixample]
Generated description
La Nova Esquerra de l'Eixample is a residential neighborhood in Barcelona’s Eixample district, known for its grid-pattern streets, mixed modernist and contemporary architecture, and vibrant local commerce.

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_69f349c880408190ade571c471ab154a completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7199bd6788190b0eb050636b84168 completed May 3, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a371850e03c819096555d7a477ad104 completed June 20, 2026, 10:46 p.m.
NEDg Description generation batch_6a3718c84ee481908c220b2564249159 completed June 20, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a37194fcaf48190b32ef74944391ffc completed June 20, 2026, 10:50 p.m.
Created at: May 1, 2026, 2:01 a.m.