Triple

T5719423
Position Surface form Disambiguated ID Type / Status
Subject Abrantes E126104 entity
Predicate hasParish P35 FINISHED
Object Alvega e Concavada
Alvega e Concavada is a civil parish in the municipality of Abrantes, in central Portugal, formed by the merger of the former parishes of Alvega and Concavada.
E540295 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: Alvega e Concavada | Statement: [Abrantes, hasParish, Alvega e Concavada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alvega e Concavada
Context triple: [Abrantes, hasParish, Alvega e Concavada]
  • A. Caleruega
    Caleruega is a small town in the province of Burgos, Spain, best known as the birthplace of Saint Dominic, founder of the Dominican Order.
  • B. Aguadas
    Aguadas is a historic Colombian town in the Caldas Department, known for its coffee culture, traditional hat-making, and well-preserved colonial architecture.
  • C. Requena
    Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
  • D. Requena
    Requena is a small Peruvian city in the Loreto region, known as a remote Amazonian river port and gateway to surrounding rainforest communities.
  • E. Cosío
    Cosío is a small municipality and town located in the northern part of the Mexican state of Aguascalientes.
  • 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: Alvega e Concavada
Triple: [Abrantes, hasParish, Alvega e Concavada]
Generated description
Alvega e Concavada is a civil parish in the municipality of Abrantes, in central Portugal, formed by the merger of the former parishes of Alvega and Concavada.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Alvega e Concavada
Target entity description: Alvega e Concavada is a civil parish in the municipality of Abrantes, in central Portugal, formed by the merger of the former parishes of Alvega and Concavada.
  • A. Caleruega
    Caleruega is a small town in the province of Burgos, Spain, best known as the birthplace of Saint Dominic, founder of the Dominican Order.
  • B. Aguadas
    Aguadas is a historic Colombian town in the Caldas Department, known for its coffee culture, traditional hat-making, and well-preserved colonial architecture.
  • C. Requena
    Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
  • D. Requena
    Requena is a small Peruvian city in the Loreto region, known as a remote Amazonian river port and gateway to surrounding rainforest communities.
  • E. Cosío
    Cosío is a small municipality and town located in the northern part of the Mexican state of Aguascalientes.
  • 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_69c0082e3d548190950169847b43043b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024e1ec7c8190a08e1b7954db2a9d completed March 22, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a7db0788190b4a5e7b5d9c94588 completed March 22, 2026, 9:09 p.m.
NEDg Description generation batch_69c05b7c3bd48190ad8303bf1bb3ec6a completed March 22, 2026, 9:13 p.m.
NED2 Entity disambiguation (via description) batch_69c05c22c31081909a9a67d99e7c728c completed March 22, 2026, 9:16 p.m.
Created at: March 22, 2026, 3:46 p.m.