Triple

T3336604
Position Surface form Disambiguated ID Type / Status
Subject Budapest Metro E70153 entity
Predicate operator P179 FINISHED
Object BKV
BKV is the main public transportation company of Budapest, Hungary, responsible for operating the city’s metro, trams, buses, and trolleybuses.
 E349652 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: BKV | Statement: [Budapest Metro, operator, BKV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BKV
Context triple: [Budapest Metro, operator, BKV]
  • A. BKL
    BKL is an alternative name for the Big Circle Line, a major circular metro line in Moscow’s rapid transit system.
  • 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. BKR
    BKR is the postal code prefix used for addresses in the town of Birkirkara in Malta.
  • D. BKR
    BKR was the abbreviated name of the People's Security Agency, an early post-World War II Indonesian security and defense organization.
  • E. Kok-boru
    Kok-boru is a traditional Central Asian horseback team game, similar to polo, in which riders compete to carry and score with a goat or sheep carcass.
  • 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: BKV
Triple: [Budapest Metro, operator, BKV]
Generated description
BKV is the main public transportation company of Budapest, Hungary, responsible for operating the city’s metro, trams, buses, and trolleybuses.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BKV
Target entity description: BKV is the main public transportation company of Budapest, Hungary, responsible for operating the city’s metro, trams, buses, and trolleybuses.
  • A. BKL
    BKL is an alternative name for the Big Circle Line, a major circular metro line in Moscow’s rapid transit system.
  • 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. BKR
    BKR is the postal code prefix used for addresses in the town of Birkirkara in Malta.
  • D. BKR
    BKR was the abbreviated name of the People's Security Agency, an early post-World War II Indonesian security and defense organization.
  • E. Kok-boru
    Kok-boru is a traditional Central Asian horseback team game, similar to polo, in which riders compete to carry and score with a goat or sheep carcass.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bad97481909359e914d44a1a74 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a8ad1a8819081d7ad2a48e2c5b9 completed March 12, 2026, 7:56 p.m.
NEDg Description generation batch_69b31c393f20819098d5761372d6a980 completed March 12, 2026, 8:04 p.m.
NED2 Entity disambiguation (via description) batch_69b3206be2748190874560701dc1ed18 completed March 12, 2026, 8:22 p.m.
Created at: March 8, 2026, 3:12 p.m.