Triple

T933444
Position Surface form Disambiguated ID Type / Status
Subject Baixa E20143 entity
Predicate borders P224 FINISHED
Object Chiado
Chiado is a historic and upscale neighborhood in central Lisbon known for its elegant shops, cafés, theaters, and literary heritage.
 E109380 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: Chiado | Statement: [Baixa, borders, Chiado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Chiado
Context triple: [Baixa, borders, Chiado]
  • A. Graça
    Graça is a historic hilltop neighborhood in Lisbon, Portugal, known for its traditional streets, viewpoints over the city, and classic tram connections.
  • B. Sabrosa
    Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
  • C. Santarém
    Santarém is a Brazilian city in the state of Pará, known for its location at the confluence of the Amazon and Tapajós rivers and its striking “meeting of the waters” phenomenon.
  • D. Beira
    Beira is a major port city in central Mozambique, serving as a key commercial and transport hub for the region.
  • E. Lourenço Marques
    Lourenço Marques is the former name of Maputo, the capital city and main port of Mozambique.
  • 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: Chiado
Triple: [Baixa, borders, Chiado]
Generated description
Chiado is a historic and upscale neighborhood in central Lisbon known for its elegant shops, cafés, theaters, and literary heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Chiado
Target entity description: Chiado is a historic and upscale neighborhood in central Lisbon known for its elegant shops, cafés, theaters, and literary heritage.
  • A. Graça
    Graça is a historic hilltop neighborhood in Lisbon, Portugal, known for its traditional streets, viewpoints over the city, and classic tram connections.
  • B. Sabrosa
    Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
  • C. Santarém
    Santarém is a Brazilian city in the state of Pará, known for its location at the confluence of the Amazon and Tapajós rivers and its striking “meeting of the waters” phenomenon.
  • D. Beira
    Beira is a major port city in central Mozambique, serving as a key commercial and transport hub for the region.
  • E. Lourenço Marques
    Lourenço Marques is the former name of Maputo, the capital city and main port of Mozambique.
  • 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_69a493af3dc48190adb7263e6e445ea1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3627ccc8190a836515b2ea85ec5 completed March 1, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7ee12da388190a26f0f7944d6f5f8 completed March 4, 2026, 8:32 a.m.
NEDg Description generation batch_69a7f12e48f88190bd0aac156a76f0b9 completed March 4, 2026, 8:45 a.m.
NED2 Entity disambiguation (via description) batch_69a7f1a2688881908524f10350137f4f completed March 4, 2026, 8:47 a.m.
Created at: March 1, 2026, 7:40 p.m.