Triple

T6056516
Position Surface form Disambiguated ID Type / Status
Subject Bamberg E134924 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object BA
BA is the vehicle registration code used on license plates for the city and district of Bamberg in Germany.
 E230928 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: BA | Statement: [Bamberg, vehicleRegistrationCode, BA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BA
Context triple: [Bamberg, vehicleRegistrationCode, BA]
  • A. BA
    BA is the New York Stock Exchange ticker symbol for The Boeing Company, a major American aerospace and defense manufacturer.
  • B. BA
    BA is the vehicle registration code used on license plates for cars registered in Bratislava, the capital city of Slovakia.
  • C. BA
    BA is the two-letter ISO 3166-1 alpha-2 country code assigned to Bosnia and Herzegovina.
  • D. BA
    BA is the commonly used abbreviation for the British Association for the Advancement of Science, a historic organization dedicated to promoting science and its understanding.
  • E. BA
    BA is the commonly used abbreviation for the British Academy, the United Kingdom’s national academy for the humanities and social sciences.
  • 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: BA
Triple: [Bamberg, vehicleRegistrationCode, BA]
Generated description
BA is the vehicle registration code used on license plates for the city and district of Bamberg in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BA
Target entity description: BA is the vehicle registration code used on license plates for the city and district of Bamberg in Germany.
  • A. BA chosen
    BA is the vehicle registration code used on license plates for the city and district of Bamberg in Upper Franconia, Germany.
  • B. BA
    BA is the vehicle registration code used on license plates for cars registered in Bratislava, the capital city of Slovakia.
  • C. BA
    BA is the two-letter ISO 3166-1 alpha-2 country code assigned to Bosnia and Herzegovina.
  • D. BA
    BA is the IATA code for British Airways, the United Kingdom’s flag carrier and one of the world’s largest international airlines.
  • E. BA
    BA is the commonly used abbreviation for the British Academy, the United Kingdom’s national academy for the humanities and social sciences.
  • F. None of above.

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_69c00877b6d4819096b0e163728b73a3 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0570bf01c8190a8b2c25b7805d403 completed March 22, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c113b06d188190839cfc48a2461d65 completed March 23, 2026, 10:19 a.m.
NEDg Description generation batch_69c114dcc99481909163f0f40f1a6358 completed March 23, 2026, 10:24 a.m.
NED2 Entity disambiguation (via description) batch_69c115552c188190b500d96e86410180 completed March 23, 2026, 10:26 a.m.
Created at: March 22, 2026, 4:09 p.m.