Triple

T8953887
Position Surface form Disambiguated ID Type / Status
Subject Alcantarilha e Pêra E213423 entity
Predicate containsSettlement P847 FINISHED
Object Pêra
Pêra is a small village in Portugal’s Algarve region, known for its traditional architecture and proximity to popular coastal and tourist areas.
 E767960 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: Pêra | Statement: [Alcantarilha e Pêra, containsSettlement, Pêra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pêra
Context triple: [Alcantarilha e Pêra, containsSettlement, Pêra]
  • A. Peperga
    Peperga is a small village in the Netherlands best known as the birthplace of Dutch colonial governor Peter Stuyvesant.
  • B. Perske
    Perske is the birth surname of American actress and cultural icon Lauren Bacall.
  • C. Pyrus
    Pyrus is a genus of flowering plants best known for including the cultivated pear trees that produce edible pears.
  • D. Pernaja
    Pernaja is a former municipality and coastal village in southern Finland, now part of the town of Loviisa.
  • E. Peren
    Peren is a town and administrative center in the northeastern Indian state of Nagaland.
  • 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: Pêra
Triple: [Alcantarilha e Pêra, containsSettlement, Pêra]
Generated description
Pêra is a small village in Portugal’s Algarve region, known for its traditional architecture and proximity to popular coastal and tourist areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pêra
Target entity description: Pêra is a small village in Portugal’s Algarve region, known for its traditional architecture and proximity to popular coastal and tourist areas.
  • A. Peperga
    Peperga is a small village in the Netherlands best known as the birthplace of Dutch colonial governor Peter Stuyvesant.
  • B. Perske
    Perske is the birth surname of American actress and cultural icon Lauren Bacall.
  • C. Pyrus
    Pyrus is a genus of flowering plants best known for including the cultivated pear trees that produce edible pears.
  • D. Pernaja
    Pernaja is a former municipality and coastal village in southern Finland, now part of the town of Loviisa.
  • E. Peren
    Peren is a town and administrative center in the northeastern Indian state of Nagaland.
  • 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_69ca8399ad2081909f8fa41d4314c215 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6724f3e4819092c6b13d80871e80 completed April 1, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc210302c8190b1c062fcbcfeb0f6 completed April 3, 2026, 1:35 p.m.
NEDg Description generation batch_69cfc34eba0881908155770166639481 completed April 3, 2026, 1:40 p.m.
NED2 Entity disambiguation (via description) batch_69cfc41fca3081908d8c2515c98283de completed April 3, 2026, 1:43 p.m.
Created at: March 30, 2026, 7 p.m.