Triple

T10258936
Position Surface form Disambiguated ID Type / Status
Subject Biblioteca Nacional de España E240543 entity
Predicate abbreviation P43 FINISHED
Object BNE
BNE is the acronym for Spain's National Library, the principal institution responsible for preserving and providing access to the country’s bibliographic heritage.
 E851614 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: BNE | Statement: [Biblioteca Nacional de España, abbreviation, BNE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BNE
Context triple: [Biblioteca Nacional de España, abbreviation, BNE]
  • A. BNE
    BNE is the three-letter IATA airport code for Brisbane Airport, the primary international and domestic airport serving Brisbane, Australia.
  • B. BPN
    BPN is the National Rail station code for Blackpool North railway station, a primary rail terminus serving the seaside town of Blackpool in Lancashire, England.
  • C. BN
    BN is the vehicle registration code used on license plates for the German city of Bonn.
  • D. BES
    BES is the international vehicle registration code used for the Caribbean Netherlands islands of Bonaire, Sint Eustatius, and Saba.
  • E. NEOB
    NEOB is a U.S. federal government office building in Washington, D.C., that houses various agencies and staff of the Executive Office of the President.
  • 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: BNE
Triple: [Biblioteca Nacional de España, abbreviation, BNE]
Generated description
BNE is the acronym for Spain's National Library, the principal institution responsible for preserving and providing access to the country’s bibliographic heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BNE
Target entity description: BNE is the acronym for Spain's National Library, the principal institution responsible for preserving and providing access to the country’s bibliographic heritage.
  • A. BNE
    BNE is the three-letter IATA airport code for Brisbane Airport, the primary international and domestic airport serving Brisbane, Australia.
  • B. BPN
    BPN is the National Rail station code for Blackpool North railway station, a primary rail terminus serving the seaside town of Blackpool in Lancashire, England.
  • C. BN
    BN is the vehicle registration code used on license plates for the German city of Bonn.
  • D. BES
    BES is the international vehicle registration code used for the Caribbean Netherlands islands of Bonaire, Sint Eustatius, and Saba.
  • E. NEOB
    NEOB is a U.S. federal government office building in Washington, D.C., that houses various agencies and staff of the Executive Office of the President.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d24e94e08190ad2b9733bf621fe4 completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f7e9a9d48190865f047750d7bc6c completed April 9, 2026, 12:50 a.m.
NEDg Description generation batch_69d6fcabb5a08190a26c068163f48878 completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d6fd7212b88190b410b8e1cc6f56fd completed April 9, 2026, 1:14 a.m.
Created at: April 6, 2026, 11:31 a.m.