Triple

T20132749
Position Surface form Disambiguated ID Type / Status
Subject Jüterbog E490937 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object TF
TF is the vehicle registration code used on license plates for the district of Teltow-Fläming in the German state of Brandenburg.
 E1413698 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: TF | Statement: [Jüterbog, vehicleRegistrationCode, TF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TF
Context triple: [Jüterbog, vehicleRegistrationCode, TF]
  • A. TF
    TF is the vehicle registration code used for motor vehicles registered in the Spanish province of Santa Cruz de Tenerife in the Canary Islands.
  • B. TF
    TF is the French abbreviation for the Federal Supreme Court of Switzerland, the country’s highest judicial authority.
  • C. TF
    TF is the abbreviation for the Faculty of Engineering at the University of Freiburg, a German institution focused on engineering and technology education and research.
  • D. TF
    TF is the IATA airline designator assigned to Braathens Regional Airlines, a Swedish regional carrier.
  • E. .tf
    .tf is the country code top-level domain (ccTLD) designated for the French Southern and Antarctic Lands, an overseas territory of France.
  • 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: TF
Triple: [Jüterbog, vehicleRegistrationCode, TF]
Generated description
TF is the vehicle registration code used on license plates for the district of Teltow-Fläming in the German state of Brandenburg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TF
Target entity description: TF is the vehicle registration code used on license plates for the district of Teltow-Fläming in the German state of Brandenburg.
  • A. TF
    TF is the vehicle registration code used for motor vehicles registered in the Spanish province of Santa Cruz de Tenerife in the Canary Islands.
  • B. TF
    TF is the French abbreviation for the Federal Supreme Court of Switzerland, the country’s highest judicial authority.
  • C. TF
    TF is the abbreviation for the Faculty of Engineering at the University of Freiburg, a German institution focused on engineering and technology education and research.
  • D. TF
    TF is the IATA airline designator assigned to Braathens Regional Airlines, a Swedish regional carrier.
  • E. .tf
    .tf is the country code top-level domain (ccTLD) designated for the French Southern and Antarctic Lands, an overseas territory of France.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66763ee908190af64af31b4ca2377 completed April 20, 2026, 5:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a082de0208c81909b9e87332d159fe0 completed May 16, 2026, 8:42 a.m.
NEDg Description generation batch_6a082f3ec3bc8190b9a499671247c02f completed May 16, 2026, 8:47 a.m.
NED2 Entity disambiguation (via description) batch_6a0830ccfdd881909cbf1c3fd2342821 completed May 16, 2026, 8:54 a.m.
Created at: April 11, 2026, 11:32 p.m.