Triple

T13862706
Position Surface form Disambiguated ID Type / Status
Subject Campanhã E333236 entity
Predicate adjacentTo P224 FINISHED
Object Paranhos
Paranhos is a civil parish in the city of Porto, Portugal, known for its residential areas and several university and hospital facilities.
E1066808 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: Paranhos | Statement: [Campanhã, adjacentTo, Paranhos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paranhos
Context triple: [Campanhã, adjacentTo, Paranhos]
  • A. Trancoso
    Trancoso is a historic Portuguese town in the Centro Region, known for its medieval walls, castle, and well-preserved old quarter.
  • B. Parecís
    Parecís is an Arawakan language spoken by the Paresí (Haliti) Indigenous people of Brazil, primarily in the state of Mato Grosso.
  • C. Putijarra
    Putijarra is an Australian Aboriginal language traditionally spoken by the Martu people of the Western Desert region.
  • D. Areias
    Areias is a neighborhood within the city of Recife, Brazil, known as part of its urban residential area.
  • E. Parea
    Parea is a small coastal village on the island of Huahine in French Polynesia, known for its tranquil beaches and traditional Polynesian atmosphere.
  • 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: Paranhos
Triple: [Campanhã, adjacentTo, Paranhos]
Generated description
Paranhos is a civil parish in the city of Porto, Portugal, known for its residential areas and several university and hospital facilities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Paranhos
Target entity description: Paranhos is a civil parish in the city of Porto, Portugal, known for its residential areas and several university and hospital facilities.
  • A. Trancoso
    Trancoso is a historic Portuguese town in the Centro Region, known for its medieval walls, castle, and well-preserved old quarter.
  • B. Parecís
    Parecís is an Arawakan language spoken by the Paresí (Haliti) Indigenous people of Brazil, primarily in the state of Mato Grosso.
  • C. Putijarra
    Putijarra is an Australian Aboriginal language traditionally spoken by the Martu people of the Western Desert region.
  • D. Areias
    Areias is a neighborhood within the city of Recife, Brazil, known as part of its urban residential area.
  • E. Parea
    Parea is a small coastal village on the island of Huahine in French Polynesia, known for its tranquil beaches and traditional Polynesian atmosphere.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c20db88190acb842748aa01039 completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0ff1f78819088ae58f703e2c9ff completed May 3, 2026, 9:41 p.m.
NEDg Description generation batch_69f7c33437e8819085b6f79402500ba3 completed May 3, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_69f7c3cd3cf0819099cc6cbd04c62e83 completed May 3, 2026, 9:53 p.m.
Created at: April 9, 2026, 10:14 p.m.