Triple

T1946784
Position Surface form Disambiguated ID Type / Status
Subject Big Circle Line E42071 entity
Predicate hasAlternativeName P39 FINISHED
Object BKL
BKL is an alternative name for the Big Circle Line, a major circular metro line in Moscow’s rapid transit system.
 E218142 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: BKL | Statement: [Big Circle Line, hasAlternativeName, BKL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BKL
Context triple: [Big Circle Line, hasAlternativeName, BKL]
  • A. BKR
    BKR was the abbreviated name of the People's Security Agency, an early post-World War II Indonesian security and defense organization.
  • B. BK
    BK is a common abbreviation for Brooklyn, a borough of New York City known for its cultural diversity, arts scene, and historic neighborhoods.
  • C. KKL
    KKL is the Hebrew acronym for Keren Kayemeth LeIsrael, the Jewish National Fund organization known for land development, afforestation, and environmental projects in Israel.
  • D. KLu
    KLu is the commonly used abbreviation for the Royal Netherlands Air Force, the aerial warfare branch of the Dutch armed forces.
  • E. k_B
    k_B is the conventional symbol used to denote the Boltzmann constant, a fundamental physical constant that relates temperature to energy at the particle level.
  • 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: BKL
Triple: [Big Circle Line, hasAlternativeName, BKL]
Generated description
BKL is an alternative name for the Big Circle Line, a major circular metro line in Moscow’s rapid transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BKL
Target entity description: BKL is an alternative name for the Big Circle Line, a major circular metro line in Moscow’s rapid transit system.
  • A. BKR
    BKR was the abbreviated name of the People's Security Agency, an early post-World War II Indonesian security and defense organization.
  • B. BK
    BK is a common abbreviation for Brooklyn, a borough of New York City known for its cultural diversity, arts scene, and historic neighborhoods.
  • C. KKL
    KKL is the Hebrew acronym for Keren Kayemeth LeIsrael, the Jewish National Fund organization known for land development, afforestation, and environmental projects in Israel.
  • D. KLu
    KLu is the commonly used abbreviation for the Royal Netherlands Air Force, the aerial warfare branch of the Dutch armed forces.
  • E. k_B
    k_B is the conventional symbol used to denote the Boltzmann constant, a fundamental physical constant that relates temperature to energy at the particle level.
  • 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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb32ebae881908f7541301f0198ae completed March 7, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfbbf724081909b24680d483edbd1 completed March 8, 2026, 10:44 p.m.
NEDg Description generation batch_69adfc6aa96c81909ae3cff6c7ab7f79 completed March 8, 2026, 10:47 p.m.
NED2 Entity disambiguation (via description) batch_69adfcebbc808190a74f9082636bce11 completed March 8, 2026, 10:49 p.m.
Created at: March 4, 2026, 7:36 p.m.