Triple

T35446446
Position Surface form Disambiguated ID Type / Status
Subject Aeropuerto Internacional de Carrasco E1024498 entity
Predicate servesRegion P82 FINISHED
Object Greater Montevideo area
The Greater Montevideo area is the main metropolitan region of Uruguay, centered on the capital city Montevideo and encompassing its surrounding urban and suburban zones.
E2147021 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: Greater Montevideo area | Statement: [Aeropuerto Internacional de Carrasco, servesRegion, Greater Montevideo 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: Greater Montevideo area
Triple: [Aeropuerto Internacional de Carrasco, servesRegion, Greater Montevideo area]
Generated description
The Greater Montevideo area is the main metropolitan region of Uruguay, centered on the capital city Montevideo and encompassing its surrounding urban and suburban zones.

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_69f76df8089481909f0018266ee881b7 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79623a6a88190bbd7f3f9e2b33304 completed May 3, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a385bc152648190aa68698866a3b2bb completed June 21, 2026, 9:46 p.m.
NEDg Description generation batch_6a385c8966a08190a3e50867b439b9a1 completed June 21, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_6a385d704a348190ba1e2de0a90f11f7 completed June 21, 2026, 9:53 p.m.
Created at: May 3, 2026, 4:04 p.m.