Triple

T31513809
Position Surface form Disambiguated ID Type / Status
Subject São Domingos de Rana E804012 entity
Predicate hasSettlement P1068 FINISHED
Object Bairro de Outeiro de Polima
Bairro de Outeiro de Polima is a residential neighborhood located within the parish of São Domingos de Rana in the municipality of Cascais, Portugal.
E1965886 NE FINISHED

How this triple was built (2 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: Bairro de Outeiro de Polima | Statement: [São Domingos de Rana, hasSettlement, Bairro de Outeiro de Polima]
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: Bairro de Outeiro de Polima
Triple: [São Domingos de Rana, hasSettlement, Bairro de Outeiro de Polima]
Generated description
Bairro de Outeiro de Polima is a residential neighborhood located within the parish of São Domingos de Rana in the municipality of Cascais, Portugal.

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_69f348ceb0a48190ae7feca263b6296c completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a2567f9c8190989b6106f8d86a9e completed May 3, 2026, 1:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b1478babc8190a20017747c581f20 completed June 11, 2026, 8:03 p.m.
NEDg Description generation batch_6a2b1977d1d08190a6a4698f97ccba4b completed June 11, 2026, 8:24 p.m.
NED2 Entity disambiguation (via description) batch_6a2b19de0240819092fd7ef4e023638f completed June 11, 2026, 8:26 p.m.
Created at: April 30, 2026, 9:51 p.m.