Triple

T16762325
Position Surface form Disambiguated ID Type / Status
Subject Quetzaltenango Department E407376 entity
Predicate hasMajorCity P316 FINISHED
Object Cabricán
Cabricán is a highland municipality and town in western Guatemala known for its indigenous culture and location within the Quetzaltenango Department.
 E1232476 NE FINISHED

How this triple was built (4 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: Cabricán | Statement: [Quetzaltenango Department, hasMajorCity, Cabricán]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cabricán
Context triple: [Quetzaltenango Department, hasMajorCity, Cabricán]
  • A. Caieta
    Caieta is an ancient coastal town in Latium, Italy—modern Gaeta—known from Roman times as a notable harbor and resort.
  • B. Es Canar
    Es Canar is a small seaside resort village on the eastern coast of Ibiza, Spain, known for its beaches and popular weekly hippy market.
  • C. Ocós
    Ocós is a coastal municipality in southwestern Guatemala known for its Pacific beaches and fishing activities.
  • D. Cabrera de Mar
    Cabrera de Mar is a coastal municipality in the Maresme comarca of Catalonia, Spain, known for its Mediterranean beaches and archaeological heritage.
  • E. Bacalar
    Bacalar is a picturesque town in Mexico’s Quintana Roo state, best known for its stunning multi-hued “Lagoon of Seven Colors” and tranquil, less-touristed atmosphere.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Cabricán
Triple: [Quetzaltenango Department, hasMajorCity, Cabricán]
Generated description
Cabricán is a highland municipality and town in western Guatemala known for its indigenous culture and location within the Quetzaltenango Department.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cabricán
Target entity description: Cabricán is a highland municipality and town in western Guatemala known for its indigenous culture and location within the Quetzaltenango Department.
  • A. Caieta
    Caieta is an ancient coastal town in Latium, Italy—modern Gaeta—known from Roman times as a notable harbor and resort.
  • B. Es Canar
    Es Canar is a small seaside resort village on the eastern coast of Ibiza, Spain, known for its beaches and popular weekly hippy market.
  • C. Ocós
    Ocós is a coastal municipality in southwestern Guatemala known for its Pacific beaches and fishing activities.
  • D. Cabrera de Mar
    Cabrera de Mar is a coastal municipality in the Maresme comarca of Catalonia, Spain, known for its Mediterranean beaches and archaeological heritage.
  • E. Bacalar
    Bacalar is a picturesque town in Mexico’s Quintana Roo state, best known for its stunning multi-hued “Lagoon of Seven Colors” and tranquil, less-touristed atmosphere.
  • F. None of above. chosen

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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3abee862c819086d9bf01e623a8ce completed April 18, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a52d077081908080c61da67e0032 completed May 10, 2026, 3:33 p.m.
NEDg Description generation batch_6a00a685753881908c3fef10823ce569 completed May 10, 2026, 3:38 p.m.
NED2 Entity disambiguation (via description) batch_6a00a7174f5c8190891ddd180c50aee3 completed May 10, 2026, 3:41 p.m.
Created at: April 10, 2026, 5:21 a.m.