Triple

T26477204
Position Surface form Disambiguated ID Type / Status
Subject Puerto Berrío E666072 entity
Predicate namedAfter P63 FINISHED
Object President Pedro Justo Berrío
President Pedro Justo Berrío was a 19th-century Colombian statesman and lawyer who served as governor of Antioquia and became known for his role in modernizing the region’s infrastructure and education.
E1725911 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: President Pedro Justo Berrío | Statement: [Puerto Berrío, namedAfter, President Pedro Justo Berrío]
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: President Pedro Justo Berrío
Triple: [Puerto Berrío, namedAfter, President Pedro Justo Berrío]
Generated description
President Pedro Justo Berrío was a 19th-century Colombian statesman and lawyer who served as governor of Antioquia and became known for his role in modernizing the region’s infrastructure and education.

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_69ee883f80dc819090e311b022b78e02 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f612cda62881909518ddc84d2efe59 completed May 2, 2026, 3:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aee7f320819083e3359d1238ab65 completed May 23, 2026, 1:43 p.m.
NEDg Description generation batch_6a11b048fe5081909c11c8996d4418af completed May 23, 2026, 1:48 p.m.
NED2 Entity disambiguation (via description) batch_6a11b18b6fdc8190801e1a7b3a296672 completed May 23, 2026, 1:54 p.m.
Created at: April 27, 2026, 12:24 a.m.