Triple

T16762312
Position Surface form Disambiguated ID Type / Status
Subject Quetzaltenango Department E407376 entity
Predicate hasMajorCity P316 FINISHED
Object Salcajá
Salcajá is a small historic city in Guatemala’s western highlands, known for its colonial church and traditional textile production.
 E1236437 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: Salcajá | Statement: [Quetzaltenango Department, hasMajorCity, Salcajá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Salcajá
Context triple: [Quetzaltenango Department, hasMajorCity, Salcajá]
  • A. Combarbalá
    Combarbalá is a small Chilean town and municipality in the Coquimbo Region, known for its semi-arid landscapes, goat farming, and distinctive combarbalite stone crafts.
  • B. Jucuna
    Jucuna is an alternative name for the Yucuna language, an indigenous Arawakan language spoken in the Amazon region of Colombia.
  • C. Jubiabá
    Jubiabá is a novel by Brazilian writer Jorge Amado that portrays Afro-Brazilian culture, social injustice, and popular resistance in Salvador, Bahia.
  • D. Ciluba
    Ciluba is a Bantu language spoken primarily in the Democratic Republic of the Congo, especially in the Kasai region.
  • E. Caxito
    Caxito is a town in northwestern Angola that serves as the administrative and economic center of Bengo Province.
  • 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: Salcajá
Triple: [Quetzaltenango Department, hasMajorCity, Salcajá]
Generated description
Salcajá is a small historic city in Guatemala’s western highlands, known for its colonial church and traditional textile production.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Salcajá
Target entity description: Salcajá is a small historic city in Guatemala’s western highlands, known for its colonial church and traditional textile production.
  • A. Combarbalá
    Combarbalá is a small Chilean town and municipality in the Coquimbo Region, known for its semi-arid landscapes, goat farming, and distinctive combarbalite stone crafts.
  • B. Jucuna
    Jucuna is an alternative name for the Yucuna language, an indigenous Arawakan language spoken in the Amazon region of Colombia.
  • C. Jubiabá
    Jubiabá is a novel by Brazilian writer Jorge Amado that portrays Afro-Brazilian culture, social injustice, and popular resistance in Salvador, Bahia.
  • D. Ciluba
    Ciluba is a Bantu language spoken primarily in the Democratic Republic of the Congo, especially in the Kasai region.
  • E. Caxito
    Caxito is a town in northwestern Angola that serves as the administrative and economic center of Bengo Province.
  • 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_6a00bb069cf481908e029b26ad96d3b5 completed May 10, 2026, 5:06 p.m.
NEDg Description generation batch_6a00bc136bfc8190ab93cd8e0e7eaf1c completed May 10, 2026, 5:10 p.m.
NED2 Entity disambiguation (via description) batch_6a00bca0a3808190be3d1d7ebd77cc20 completed May 10, 2026, 5:13 p.m.
Created at: April 10, 2026, 5:21 a.m.