Triple

T15003423
Position Surface form Disambiguated ID Type / Status
Subject Pombal E374146 entity
Predicate hasPart P35 FINISHED
Object Louriçal
Louriçal is a civil parish in the municipality of Pombal, in Portugal’s Leiria District, known for its rural character and historical religious architecture.
 E1134236 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: Louriçal | Statement: [Pombal, hasPart, Louriçal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Louriçal
Context triple: [Pombal, hasPart, Louriçal]
  • A. Raposeira
    Raposeira is a small village in Portugal’s Algarve region, known for its rural charm and proximity to the Atlantic coast near Vila do Bispo.
  • B. Paranhos
    Paranhos is a civil parish in the city of Porto, Portugal, known for its residential areas and several university and hospital facilities.
  • C. 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.
  • D. Loure
    The Loure is a slow, stately French Baroque dance in compound duple meter, characterized by its dotted rhythms and often pastoral character.
  • E. Caieiras
    Caieiras is a municipality in the metropolitan region of São Paulo, Brazil, known for its industrial activity and surrounding green areas.
  • 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: Louriçal
Triple: [Pombal, hasPart, Louriçal]
Generated description
Louriçal is a civil parish in the municipality of Pombal, in Portugal’s Leiria District, known for its rural character and historical religious architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Louriçal
Target entity description: Louriçal is a civil parish in the municipality of Pombal, in Portugal’s Leiria District, known for its rural character and historical religious architecture.
  • A. Raposeira
    Raposeira is a small village in Portugal’s Algarve region, known for its rural charm and proximity to the Atlantic coast near Vila do Bispo.
  • B. Paranhos
    Paranhos is a civil parish in the city of Porto, Portugal, known for its residential areas and several university and hospital facilities.
  • C. 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.
  • D. Loure
    The Loure is a slow, stately French Baroque dance in compound duple meter, characterized by its dotted rhythms and often pastoral character.
  • E. Caieiras
    Caieiras is a municipality in the metropolitan region of São Paulo, Brazil, known for its industrial activity and surrounding green areas.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7312ae48190bdaf91ecced6657e completed April 15, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dcbd7c88190ad1a302cd0c6ef28 completed May 9, 2026, 2:37 a.m.
NEDg Description generation batch_69fe9e8eb3608190b26692e5ce2b0643 completed May 9, 2026, 2:40 a.m.
NED2 Entity disambiguation (via description) batch_69fe9f1e9010819092a9d39b85b30f2b completed May 9, 2026, 2:42 a.m.
Created at: April 10, 2026, 2:54 a.m.