Triple

T3608757
Position Surface form Disambiguated ID Type / Status
Subject Centro Region E76433 entity
Predicate containsCity P294 FINISHED
Object Mação
Mação is a municipality in central Portugal known for its rural landscapes, archaeological heritage, and traditional villages.
 E374170 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: Mação | Statement: [Centro Region, containsCity, Mação]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mação
Context triple: [Centro Region, containsCity, Mação]
  • A. Caieiras
    Caieiras is a municipality in the metropolitan region of São Paulo, Brazil, known for its industrial activity and surrounding green areas.
  • B. Mexilhoeira Grande
    Mexilhoeira Grande is a civil parish in Portugal’s Algarve region known for its traditional village character and nearby archaeological sites.
  • C. Capileira
    Capileira is a picturesque mountain village in Spain’s Alpujarras region, known for its traditional whitewashed houses and dramatic location on the southern slopes of the Sierra Nevada.
  • D. Bérrio
    Bérrio was a Portuguese carrack that served as one of the ships in Vasco da Gama’s pioneering fleet on the first voyage from Portugal to India.
  • E. Cabaceiras
    Cabaceiras is a historic town in the Brazilian state of Paraíba, known for its well-preserved colonial architecture and frequent use as a filming location for movies and television.
  • 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: Mação
Triple: [Centro Region, containsCity, Mação]
Generated description
Mação is a municipality in central Portugal known for its rural landscapes, archaeological heritage, and traditional villages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mação
Target entity description: Mação is a municipality in central Portugal known for its rural landscapes, archaeological heritage, and traditional villages.
  • A. Caieiras
    Caieiras is a municipality in the metropolitan region of São Paulo, Brazil, known for its industrial activity and surrounding green areas.
  • B. Mexilhoeira Grande
    Mexilhoeira Grande is a civil parish in Portugal’s Algarve region known for its traditional village character and nearby archaeological sites.
  • C. Capileira
    Capileira is a picturesque mountain village in Spain’s Alpujarras region, known for its traditional whitewashed houses and dramatic location on the southern slopes of the Sierra Nevada.
  • D. Bérrio
    Bérrio was a Portuguese carrack that served as one of the ships in Vasco da Gama’s pioneering fleet on the first voyage from Portugal to India.
  • E. Cabaceiras
    Cabaceiras is a historic town in the Brazilian state of Paraíba, known for its well-preserved colonial architecture and frequent use as a filming location for movies and television.
  • 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_69ad85da0ba481908b3b48c69efe2b98 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc22a3cf081908c20b6fb55be0db2 completed March 8, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4330de7a08190933aa7e9dc0a65be completed March 13, 2026, 3:53 p.m.
NEDg Description generation batch_69b437cf839881909b1d505328285123 completed March 13, 2026, 4:14 p.m.
NED2 Entity disambiguation (via description) batch_69b43835994c81909230bbb21b12b8ef completed March 13, 2026, 4:15 p.m.
Created at: March 8, 2026, 3:22 p.m.