Triple

T9714030
Position Surface form Disambiguated ID Type / Status
Subject Gmund am Tegernsee E235092 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object MB
MB is the vehicle registration code for the district of Miesbach in Bavaria, Germany.
 E817024 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: MB | Statement: [Gmund am Tegernsee, vehicleRegistrationCode, MB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MB
Context triple: [Gmund am Tegernsee, vehicleRegistrationCode, MB]
  • A. MB
    MB is the official two-letter Canada Post abbreviation used to designate the province of Manitoba in mailing addresses and postal codes.
  • B. MMB
    MMB is the stock ticker symbol for Lagardère Group, a major French media and publishing conglomerate.
  • C. MMB
    MMB is the commonly used abbreviation for the Michigan Marching Band, the official marching band of the University of Michigan known for its performances at football games and major events.
  • D. MBZ
    MBZ is the widely used acronym for Mohamed bin Zayed Al Nahyan, the President of the United Arab Emirates and Ruler of Abu Dhabi.
  • E. BM
    BM is the regional vehicle registration code used on license plates for motor vehicles registered in Pekanbaru, Indonesia.
  • 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: MB
Triple: [Gmund am Tegernsee, vehicleRegistrationCode, MB]
Generated description
MB is the vehicle registration code for the district of Miesbach in Bavaria, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MB
Target entity description: MB is the vehicle registration code for the district of Miesbach in Bavaria, Germany.
  • A. MB
    MB is the official two-letter Canada Post abbreviation used to designate the province of Manitoba in mailing addresses and postal codes.
  • B. MMB
    MMB is the stock ticker symbol for Lagardère Group, a major French media and publishing conglomerate.
  • C. MMB
    MMB is the commonly used abbreviation for the Michigan Marching Band, the official marching band of the University of Michigan known for its performances at football games and major events.
  • D. MBZ
    MBZ is the widely used acronym for Mohamed bin Zayed Al Nahyan, the President of the United Arab Emirates and Ruler of Abu Dhabi.
  • E. BM
    BM is the abbreviated name of Hungary’s Ministry of the Interior, the government body responsible for internal affairs, law enforcement, and public administration.
  • 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_69ca84cd8fa0819090a5e243ceb37003 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e087a1c8190aa62c910f88e8516 completed April 1, 2026, 10:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f900ca08190a52f042feab2afa3 completed April 4, 2026, 11:32 p.m.
NEDg Description generation batch_69d1a181f10081908bfb0fae5a08462f completed April 4, 2026, 11:40 p.m.
NED2 Entity disambiguation (via description) batch_69d1a228b8488190a5a61f3468e92649 completed April 4, 2026, 11:43 p.m.
Created at: March 30, 2026, 8:19 p.m.