Triple

T2164437
Position Surface form Disambiguated ID Type / Status
Subject Marburg, Hesse, Germany E46876 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object MR
MR is the official vehicle registration code used on license plates for the city of Marburg in the German state of Hesse.
 E239054 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: MR | Statement: [Marburg, Hesse, Germany, vehicleRegistrationCode, MR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MR
Context triple: [Marburg, Hesse, Germany, vehicleRegistrationCode, MR]
  • A. MR
    MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
  • B. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • C. M
    M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
  • D. M
    "M" is a 1951 American crime thriller film directed by Joseph Losey, adapted from Fritz Lang’s 1931 classic, in which David Wayne portrays a hunted child murderer.
  • E. M
    M is a New York City Subway service that runs along the IND Sixth Avenue Line in Manhattan and connects Brooklyn and Queens.
  • 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: MR
Triple: [Marburg, Hesse, Germany, vehicleRegistrationCode, MR]
Generated description
MR is the official vehicle registration code used on license plates for the city of Marburg in the German state of Hesse.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MR
Target entity description: MR is the official vehicle registration code used on license plates for the city of Marburg in the German state of Hesse.
  • A. MR
    MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
  • B. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • C. M
    M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
  • D. M
    "M" is a 1951 American crime thriller film directed by Joseph Losey, adapted from Fritz Lang’s 1931 classic, in which David Wayne portrays a hunted child murderer.
  • E. M
    M is a New York City Subway service that runs along the IND Sixth Avenue Line in Manhattan and connects Brooklyn and Queens.
  • 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_69a88a184cbc8190877791f6552c2484 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe8e1cfc81908adc0357ddfec701 completed March 7, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae58ee18ac81909f02e2c87000365b completed March 9, 2026, 5:21 a.m.
NEDg Description generation batch_69ae597198b88190b0253aa121ed35e1 completed March 9, 2026, 5:24 a.m.
NED2 Entity disambiguation (via description) batch_69ae5a02404c819088acf7c592cb2cae completed March 9, 2026, 5:26 a.m.
Created at: March 4, 2026, 7:45 p.m.