Triple

T8277322
Position Surface form Disambiguated ID Type / Status
Subject Beaverton City Library E193577 entity
Predicate abbreviation P43 FINISHED
Object BCL
BCL is a public library system serving the community of Beaverton, Oregon with lending materials, programs, and educational resources.
E723114 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: BCL | Statement: [Beaverton City Library, abbreviation, BCL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BCL
Context triple: [Beaverton City Library, abbreviation, BCL]
  • A. BLC
    BLC is the commonly used abbreviation for the Boston Landmarks Commission, the city agency responsible for identifying and protecting Boston’s historic buildings and districts.
  • B. BRL
    BRL is the official currency code for the Brazilian real, the legal tender of Brazil.
  • C. BKL
    BKL is an alternative name for the Big Circle Line, a major circular metro line in Moscow’s rapid transit system.
  • D. BKL
    BKL is the FAA airport code for Burke Lakefront Airport, a public airport located on the shore of Lake Erie in Cleveland, Ohio.
  • E. BL
    BL is the commonly used abbreviation for British Leyland, a major former UK vehicle manufacturer known for producing a wide range of cars, trucks, and buses in the 20th century.
  • 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: BCL
Triple: [Beaverton City Library, abbreviation, BCL]
Generated description
BCL is a public library system serving the community of Beaverton, Oregon with lending materials, programs, and educational resources.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BCL
Target entity description: BCL is a public library system serving the community of Beaverton, Oregon with lending materials, programs, and educational resources.
  • A. BLC
    BLC is the commonly used abbreviation for the Boston Landmarks Commission, the city agency responsible for identifying and protecting Boston’s historic buildings and districts.
  • B. BRL
    BRL is the official currency code for the Brazilian real, the legal tender of Brazil.
  • C. BKL
    BKL is an alternative name for the Big Circle Line, a major circular metro line in Moscow’s rapid transit system.
  • D. BKL
    BKL is the FAA airport code for Burke Lakefront Airport, a public airport located on the shore of Lake Erie in Cleveland, Ohio.
  • E. BL
    BL is the commonly used abbreviation for British Leyland, a major former UK vehicle manufacturer known for producing a wide range of cars, trucks, and buses in the 20th century.
  • 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_69ca82e217a48190880695635c44b2ed completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb79ea3fb481908b59414702a5147e completed March 31, 2026, 7:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd6859cbc48190835dffa7de054d15 completed April 1, 2026, 6:47 p.m.
NEDg Description generation batch_69cd6d52763c8190891f88d62be44786 completed April 1, 2026, 7:09 p.m.
NED2 Entity disambiguation (via description) batch_69cd7e0d1b8c8190b5183cc176432061 completed April 1, 2026, 8:20 p.m.
Created at: March 30, 2026, 5:51 p.m.