Triple

T12279210
Position Surface form Disambiguated ID Type / Status
Subject Büdesheim E292671 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object BIT
BIT is the vehicle registration code for the district of Bitburg-Prüm in the German state of Rhineland-Palatinate.
E975936 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: BIT | Statement: [Büdesheim, vehicleRegistrationCode, BIT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BIT
Context triple: [Büdesheim, vehicleRegistrationCode, BIT]
  • A. BIT
    BIT is the stock exchange code commonly used to identify securities listed on Borsa Italiana, the main Italian stock exchange based in Milan.
  • B. BITS
    BITS (Background Intelligent Transfer Service) is a Windows component that transfers files in the background using idle network bandwidth to minimize impact on other network activity.
  • C. BITC
    BITC (Burnt-In Timecode) is a visual representation of timecode numbers superimposed directly onto video frames for easy reference during editing and review.
  • D. BitC
    BitC is a systems programming language designed for safety, low-level control, and formal verification, drawing on ideas from Modula-3 and capability-based security.
  • E. BIN
    BIN is the vehicle registration code used on license plates for vehicles registered in the town of Ingelheim am Rhein in Germany.
  • 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: BIT
Triple: [Büdesheim, vehicleRegistrationCode, BIT]
Generated description
BIT is the vehicle registration code for the district of Bitburg-Prüm in the German state of Rhineland-Palatinate.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BIT
Target entity description: BIT is the vehicle registration code for the district of Bitburg-Prüm in the German state of Rhineland-Palatinate.
  • A. BIT
    BIT is the stock exchange code commonly used to identify securities listed on Borsa Italiana, the main Italian stock exchange based in Milan.
  • B. BITS
    BITS (Background Intelligent Transfer Service) is a Windows component that transfers files in the background using idle network bandwidth to minimize impact on other network activity.
  • C. BITC
    BITC (Burnt-In Timecode) is a visual representation of timecode numbers superimposed directly onto video frames for easy reference during editing and review.
  • D. BitC
    BitC is a systems programming language designed for safety, low-level control, and formal verification, drawing on ideas from Modula-3 and capability-based security.
  • E. BIN
    BIN is the vehicle registration code used on license plates for vehicles registered in the town of Ingelheim am Rhein in Germany.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cf1ab8c8190a51f498bfda957d8 completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e6f46f08190839ba07ef6fac984 completed May 2, 2026, 3:55 p.m.
NEDg Description generation batch_69f622de74f0819096c5f5bf6f938fe7 completed May 2, 2026, 4:14 p.m.
NED2 Entity disambiguation (via description) batch_69f62379746c8190bc9da48775b86dfa completed May 2, 2026, 4:16 p.m.
Created at: April 8, 2026, 9:52 p.m.