Triple

T16644513
Position Surface form Disambiguated ID Type / Status
Subject Bayerischer Platz station E404431 entity
Predicate hasStationCode P1289 FINISHED
Object BPL
BPL is the station code for Bayerischer Platz, a Berlin U-Bahn station in Germany.
 E1226369 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: BPL | Statement: [Bayerischer Platz station, hasStationCode, BPL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BPL
Context triple: [Bayerischer Platz station, hasStationCode, BPL]
  • A. BUPL
    BUPL is a Danish trade union representing early childhood educators and pedagogical staff.
  • B. BVL
    BVL is Germany’s Federal Office of Consumer Protection and Food Safety, the national authority responsible for ensuring food safety and protecting consumer health.
  • C. BPC
    BPC is the commonly used abbreviation for the Bryant Park Corporation, the nonprofit organization that manages and maintains Bryant Park in New York City.
  • D. BL
    BL is the vehicle registration code used for the city of Banja Luka in Bosnia and Herzegovina.
  • E. BL
    BL is the postcode area in the United Kingdom that covers Bolton and surrounding parts of Greater Manchester and Lancashire.
  • 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: BPL
Triple: [Bayerischer Platz station, hasStationCode, BPL]
Generated description
BPL is the station code for Bayerischer Platz, a Berlin U-Bahn station in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BPL
Target entity description: BPL is the station code for Bayerischer Platz, a Berlin U-Bahn station in Germany.
  • A. BUPL
    BUPL is a Danish trade union representing early childhood educators and pedagogical staff.
  • B. BVL
    BVL is Germany’s Federal Office of Consumer Protection and Food Safety, the national authority responsible for ensuring food safety and protecting consumer health.
  • C. BPC
    BPC is the commonly used abbreviation for the Bryant Park Corporation, the nonprofit organization that manages and maintains Bryant Park in New York City.
  • D. BL
    BL is the vehicle registration code used for the city of Banja Luka in Bosnia and Herzegovina.
  • E. BL
    BL is the postcode area in the United Kingdom that covers Bolton and surrounding parts of Greater Manchester and Lancashire.
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ad4735c81908a3a227bf02ca489 completed April 18, 2026, 12:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084bf0900819092db11456eb8e1c0 completed May 10, 2026, 1:14 p.m.
NEDg Description generation batch_6a00862fe04481908bc114001357aea9 completed May 10, 2026, 1:20 p.m.
NED2 Entity disambiguation (via description) batch_6a00879d9f948190bdf40ff7be2505ff completed May 10, 2026, 1:26 p.m.
Created at: April 10, 2026, 5:18 a.m.