Triple

T1383863
Position Surface form Disambiguated ID Type / Status
Subject San José E29798 entity
Predicate hasDistrict P459 FINISHED
Object Zapote
Zapote is a district of San José, Costa Rica, known for housing important government buildings and urban residential areas.
 E162585 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: Zapote | Statement: [San José, hasDistrict, Zapote]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zapote
Context triple: [San José, hasDistrict, Zapote]
  • A. Topolobampo
    Topolobampo is a major Pacific coast port city in northwestern Mexico, serving as an important hub for maritime trade and ferry connections in the state of Sinaloa.
  • B. Tecuala
    Tecuala is a municipality and town in the Mexican state of Nayarit, known for its agricultural activities and proximity to coastal wetlands along the Pacific.
  • C. Tejipió
    Tejipió is a neighborhood in the city of Recife, Brazil, known as part of the urban fabric of the state capital of Pernambuco.
  • D. Mocorito
    Mocorito is a historic town and municipality in the Mexican state of Sinaloa, known for its colonial architecture and cultural traditions.
  • E. Mexican Cocopa
    Mexican Cocopa is a regional variety of the Cocopa language spoken by Cocopa communities in northern Mexico.
  • 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: Zapote
Triple: [San José, hasDistrict, Zapote]
Generated description
Zapote is a district of San José, Costa Rica, known for housing important government buildings and urban residential areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zapote
Target entity description: Zapote is a district of San José, Costa Rica, known for housing important government buildings and urban residential areas.
  • A. Topolobampo
    Topolobampo is a major Pacific coast port city in northwestern Mexico, serving as an important hub for maritime trade and ferry connections in the state of Sinaloa.
  • B. Tecuala
    Tecuala is a municipality and town in the Mexican state of Nayarit, known for its agricultural activities and proximity to coastal wetlands along the Pacific.
  • C. Tejipió
    Tejipió is a neighborhood in the city of Recife, Brazil, known as part of the urban fabric of the state capital of Pernambuco.
  • D. Mocorito
    Mocorito is a historic town and municipality in the Mexican state of Sinaloa, known for its colonial architecture and cultural traditions.
  • E. Mexican Cocopa
    Mexican Cocopa is a regional variety of the Cocopa language spoken by Cocopa communities in northern Mexico.
  • 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_69a498dc92f8819094a1108f8ac90f43 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c3377b608190b915e6871c1fe86e completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace56940408190aeba5a342ae3ab17 completed March 8, 2026, 2:56 a.m.
NEDg Description generation batch_69ace5fb515081908acadef0303b8f6e completed March 8, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_69ace9ba4b3481908d03636d8f72d04c completed March 8, 2026, 3:15 a.m.
Created at: March 1, 2026, 7:59 p.m.