Triple

T65274
Position Surface form Disambiguated ID Type / Status
Subject Coimbra Group E1299 entity
Predicate foundedInCity P263 FINISHED
Object Coimbra
Coimbra is a historic Portuguese city known for its medieval architecture and the University of Coimbra, one of the oldest universities in continuous operation in the world.
 E12101 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: Coimbra | Statement: [Coimbra Group, foundedInCity, Coimbra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Coimbra
Context triple: [Coimbra Group, foundedInCity, Coimbra]
  • A. Lisbon
    Lisbon is the coastal capital city of Portugal, renowned for its historic architecture, hilly landscape, and role as a major cultural and economic center in Europe.
  • B. Sabrosa
    Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
  • C. Albufeira
    Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
  • D. Valladolid
    Valladolid is a historic city in northwestern Spain that served as a major political and cultural center, including as a former capital of the Spanish monarchy.
  • E. Algarve
    Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
  • 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: Coimbra
Triple: [Coimbra Group, foundedInCity, Coimbra]
Generated description
Coimbra is a historic Portuguese city known for its medieval architecture and the University of Coimbra, one of the oldest universities in continuous operation in the world.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Coimbra
Target entity description: Coimbra is a historic Portuguese city known for its medieval architecture and the University of Coimbra, one of the oldest universities in continuous operation in the world.
  • A. Lisbon
    Lisbon is the coastal capital city of Portugal, renowned for its historic architecture, hilly landscape, and role as a major cultural and economic center in Europe.
  • B. Sabrosa
    Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
  • C. Albufeira
    Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
  • D. Valladolid
    Valladolid is a historic city in northwestern Spain that served as a major political and cultural center, including as a former capital of the Spanish monarchy.
  • E. Algarve
    Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
  • 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_69a24ba4f760819081f6638a3c70538a completed Feb. 28, 2026, 1:57 a.m.
NER Named-entity recognition batch_69a24ee6ba348190b00977285d74d8f5 completed Feb. 28, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a284fb8c1481908d7796593836c925 completed Feb. 28, 2026, 6:02 a.m.
NEDg Description generation batch_69a2860807c48190a0073124dba847e7 completed Feb. 28, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_69a286c53b348190bcec6ff70fa3ac16 completed Feb. 28, 2026, 6:10 a.m.
Created at: Feb. 28, 2026, 2:02 a.m.