Triple

T34721970
Position Surface form Disambiguated ID Type / Status
Subject Avenida Ricardo Lyon E1000940 entity
Predicate hasIntersectionWith P13379 FINISHED
Object Avenida Francisco Bilbao
Avenida Francisco Bilbao is a major east–west thoroughfare in Santiago, Chile, running through several central and eastern communes and serving as an important residential and commercial corridor.
E2285182 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: Avenida Francisco Bilbao | Statement: [Avenida Ricardo Lyon, hasIntersectionWith, Avenida Francisco Bilbao]
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: Avenida Francisco Bilbao
Triple: [Avenida Ricardo Lyon, hasIntersectionWith, Avenida Francisco Bilbao]
Generated description
Avenida Francisco Bilbao is a major east–west thoroughfare in Santiago, Chile, running through several central and eastern communes and serving as an important residential and commercial corridor.

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_69f76daeb6e48190a4c9a6b0edc80f72 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77994a2248190bcc37dbbf6750a6f completed May 3, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a45030830e0819086aea974d7b7e85d completed July 1, 2026, 12:07 p.m.
NEDg Description generation batch_6a4506e718588190835a4bd44a4f15d3 completed July 1, 2026, 12:24 p.m.
NED2 Entity disambiguation (via description) batch_6a453f3cc50881908a4274a365d7a1c9 completed July 1, 2026, 4:24 p.m.
Created at: May 3, 2026, 3:59 p.m.