Triple

T34218975
Position Surface form Disambiguated ID Type / Status
Subject Comuna 12 of Buenos Aires E877872 entity
Predicate containsNeighborhood P4813 FINISHED
Object Villa Pueyrredón
Villa Pueyrredón is a primarily residential neighborhood in the northern part of Buenos Aires, Argentina, known for its quiet streets, local commerce, and strong community atmosphere.
E2088269 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: Villa Pueyrredón | Statement: [Comuna 12 of Buenos Aires, containsNeighborhood, Villa Pueyrredón]
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: Villa Pueyrredón
Triple: [Comuna 12 of Buenos Aires, containsNeighborhood, Villa Pueyrredón]
Generated description
Villa Pueyrredón is a primarily residential neighborhood in the northern part of Buenos Aires, Argentina, known for its quiet streets, local commerce, and strong community atmosphere.

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_69f349b0b4bc819088c1552424089ee9 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71080959c81909be22e06eb0bc03d completed May 3, 2026, 9:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36d5df1bf081908a08af474ebc0c5e completed June 20, 2026, 6:03 p.m.
NEDg Description generation batch_6a36d67057948190a84e145cfb4a21da completed June 20, 2026, 6:05 p.m.
NED2 Entity disambiguation (via description) batch_6a36d6dc9d50819086675a90c00b5889 completed June 20, 2026, 6:07 p.m.
Created at: May 1, 2026, 1:55 a.m.