Triple

T13769243
Position Surface form Disambiguated ID Type / Status
Subject Cortés Department E330832 entity
Predicate containsCity P294 FINISHED
Object La Lima
La Lima is a Honduran city in the Cortés Department known for its banana industry and proximity to San Pedro Sula.
 E1060756 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: La Lima | Statement: [Cortés Department, containsCity, La Lima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: La Lima
Context triple: [Cortés Department, containsCity, La Lima]
  • A. Cono Oeste of Lima
    Cono Oeste of Lima is a western metropolitan sector of Peru’s capital that groups several coastal and urban districts, including San Miguel, for planning and administrative purposes.
  • B. Sucre
    Sucre is a coastal state in northeastern Venezuela known for its Caribbean shoreline, fishing communities, and colonial-era towns.
  • C. Sucre
    Sucre is the constitutional capital of Bolivia, known for its well-preserved colonial architecture and historical significance in the country’s independence.
  • D. Chacao
    Chacao is a coastal town in southern Chile located on the northern tip of Chiloé Island, known for its strategic position by the Chacao Channel.
  • E. Juliaca
    Juliaca is a major commercial and transportation hub in southern Peru, known for its bustling markets and proximity to Lake Titicaca.
  • 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: La Lima
Triple: [Cortés Department, containsCity, La Lima]
Generated description
La Lima is a Honduran city in the Cortés Department known for its banana industry and proximity to San Pedro Sula.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: La Lima
Target entity description: La Lima is a Honduran city in the Cortés Department known for its banana industry and proximity to San Pedro Sula.
  • A. Cono Oeste of Lima
    Cono Oeste of Lima is a western metropolitan sector of Peru’s capital that groups several coastal and urban districts, including San Miguel, for planning and administrative purposes.
  • B. Sucre
    Sucre is a coastal state in northeastern Venezuela known for its Caribbean shoreline, fishing communities, and colonial-era towns.
  • C. Sucre
    Sucre is the constitutional capital of Bolivia, known for its well-preserved colonial architecture and historical significance in the country’s independence.
  • D. Chacao
    Chacao is a coastal town in southern Chile located on the northern tip of Chiloé Island, known for its strategic position by the Chacao Channel.
  • E. Juliaca
    Juliaca is a major commercial and transportation hub in southern Peru, known for its bustling markets and proximity to Lake Titicaca.
  • 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_69d81c583b0081909e408a17db517a21 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0233ecc48190b934f085d2501eb1 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b0724ab481908448d71a1bd02253 completed May 3, 2026, 8:30 p.m.
NEDg Description generation batch_69f7b0f912f081908084042860c922cb completed May 3, 2026, 8:32 p.m.
NED2 Entity disambiguation (via description) batch_69f7b16a43188190968d5cdf32e447ec completed May 3, 2026, 8:34 p.m.
Created at: April 9, 2026, 10:10 p.m.