Triple

T14259605
Position Surface form Disambiguated ID Type / Status
Subject Chocó family E353476 entity
Predicate hasPart P35 FINISHED
Object Epena Emberá
Epena Emberá is an indigenous Chocoan language spoken by the Emberá people primarily in Colombia and Panama.
 E1089804 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: Epena Emberá | Statement: [Chocó family, hasPart, Epena Emberá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Epena Emberá
Context triple: [Chocó family, hasPart, Epena Emberá]
  • A. Balbuena
    Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • B. Erba
    Erba is a town in the Lombardy region of northern Italy, situated near Lake Como and known for its scenic surroundings and local industry.
  • C. Pacasmayo
    Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
  • D. Guayzimi
    Guayzimi is a small town in southeastern Ecuador that serves as an administrative and commercial center in the Amazonian region of Zamora-Chinchipe Province.
  • E. Cajeme
    Cajeme is a major municipality and agricultural and industrial center in the southern part of the Mexican state of Sonora, best known for its main city Ciudad Obregón.
  • 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: Epena Emberá
Triple: [Chocó family, hasPart, Epena Emberá]
Generated description
Epena Emberá is an indigenous Chocoan language spoken by the Emberá people primarily in Colombia and Panama.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Epena Emberá
Target entity description: Epena Emberá is an indigenous Chocoan language spoken by the Emberá people primarily in Colombia and Panama.
  • A. Balbuena
    Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • B. Erba
    Erba is a town in the Lombardy region of northern Italy, situated near Lake Como and known for its scenic surroundings and local industry.
  • C. Pacasmayo
    Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
  • D. Guayzimi
    Guayzimi is a small town in southeastern Ecuador that serves as an administrative and commercial center in the Amazonian region of Zamora-Chinchipe Province.
  • E. Cajeme
    Cajeme is a major municipality and agricultural and industrial center in the southern part of the Mexican state of Sonora, best known for its main city Ciudad Obregón.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de635534988190816fdfb315cd2a3f completed April 14, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3260fdf88190b482480a17bd6674 completed May 8, 2026, 12:46 a.m.
NEDg Description generation batch_69fd33cba18481908f2dfe358017f11b completed May 8, 2026, 12:52 a.m.
NED2 Entity disambiguation (via description) batch_69fd346ffb9c81909ec28e514ea5451b completed May 8, 2026, 12:55 a.m.
Created at: April 10, 2026, 1:09 a.m.