Triple

T15567577
Position Surface form Disambiguated ID Type / Status
Subject Ourém E374155 entity
Predicate contains P35 FINISHED
Object Caxarias
Caxarias is a civil parish and locality within the municipality of Ourém in central Portugal.
E1166605 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: Caxarias | Statement: [Ourém, contains, Caxarias]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caxarias
Context triple: [Ourém, contains, Caxarias]
  • A. Caxito
    Caxito is a town in northwestern Angola that serves as the administrative and economic center of Bengo Province.
  • B. Cayastá
    Cayastá is a small town in Argentina’s Santa Fe Province known for its proximity to the historic Santa Fe La Vieja archaeological site, which preserves the remains of one of the region’s earliest Spanish settlements.
  • C. Chinandega
    Chinandega is a city in northwestern Nicaragua known as a commercial and agricultural hub near the country’s highest volcanoes.
  • D. Caxangá
    Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
  • E. Tuyuca
    Tuyuca is an indigenous Eastern Tucanoan language spoken primarily in the Amazon region of Colombia and Brazil, noted for its complex verb morphology and extensive evidentiality system.
  • 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: Caxarias
Triple: [Ourém, contains, Caxarias]
Generated description
Caxarias is a civil parish and locality within the municipality of Ourém in central Portugal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Caxarias
Target entity description: Caxarias is a civil parish and locality within the municipality of Ourém in central Portugal.
  • A. Caxito
    Caxito is a town in northwestern Angola that serves as the administrative and economic center of Bengo Province.
  • B. Cayastá
    Cayastá is a small town in Argentina’s Santa Fe Province known for its proximity to the historic Santa Fe La Vieja archaeological site, which preserves the remains of one of the region’s earliest Spanish settlements.
  • C. Chinandega
    Chinandega is a city in northwestern Nicaragua known as a commercial and agricultural hub near the country’s highest volcanoes.
  • D. Caxangá
    Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
  • E. Tuyuca
    Tuyuca is an indigenous Eastern Tucanoan language spoken primarily in the Amazon region of Colombia and Brazil, noted for its complex verb morphology and extensive evidentiality system.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04dde90b081908284d9258d4462e3 completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56c231e0819083d6032eb21114b2 completed May 9, 2026, 3:46 p.m.
NEDg Description generation batch_69ff58334f688190907e331755156c8a completed May 9, 2026, 3:52 p.m.
NED2 Entity disambiguation (via description) batch_69ff588814808190a7e593a5ae80f816 completed May 9, 2026, 3:53 p.m.
Created at: April 10, 2026, 4:10 a.m.