Triple

T24689740
Position Surface form Disambiguated ID Type / Status
Subject Virú Province E611399 entity
Predicate locatedIn P40 FINISHED
Object La Libertad Department
La Libertad Department is a coastal administrative region in northwestern Peru known for its capital city Trujillo, rich pre-Columbian archaeological sites, and agricultural production.
 E1880272 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 Libertad Department | Statement: [Virú Province, locatedIn, La Libertad Department]
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 Libertad Department
Triple: [Virú Province, locatedIn, La Libertad Department]
Generated description
La Libertad Department is a coastal administrative region in northwestern Peru known for its capital city Trujillo, rich pre-Columbian archaeological sites, and agricultural production.

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_69e2c4d678b081908910f4271627a31a completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40fc8da0c81908aa28a098a36758e completed May 1, 2026, 2:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a267e87f534819095c8af1d0e95de86 completed June 8, 2026, 8:34 a.m.
NEDg Description generation batch_6a2682fadaf48190a4d691901671b579 completed June 8, 2026, 8:53 a.m.
NED2 Entity disambiguation (via description) batch_6a268ec8f3908190a8801d62e978ac15 completed June 8, 2026, 9:43 a.m.
Created at: April 18, 2026, 3:20 a.m.