Triple

T9223389
Position Surface form Disambiguated ID Type / Status
Subject Lauterach E221617 entity
Predicate vehicleRegistrationCodeDistrict P43726 FINISHED
Object UL
UL is the vehicle registration code for the district that includes the municipality of Lauterach in Austria.
E786793 NE FINISHED

How this triple was built (5 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: UL | Statement: [Lauterach, vehicleRegistrationCodeDistrict, UL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UL
Context triple: [Lauterach, vehicleRegistrationCodeDistrict, UL]
  • A. UL
    UL is the vehicle registration code used on license plates for the city of Ulm in Germany.
  • B. UL
    UL is the two-letter IATA airline designator assigned to SriLankan Airlines, the flag carrier of Sri Lanka.
  • C. UL
    UL is the New York Stock Exchange ticker symbol for Unilever, a major multinational consumer goods company known for its food, personal care, and household products.
  • D. LU
    LU is the vehicle registration code for the German city of Ludwigshafen am Rhein in the state of Rhineland-Palatinate.
  • E. LU
    LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
  • 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: UL
Triple: [Lauterach, vehicleRegistrationCodeDistrict, UL]
Generated description
UL is the vehicle registration code for the district that includes the municipality of Lauterach in Austria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: UL
Target entity description: UL is the vehicle registration code for the district that includes the municipality of Lauterach in Austria.
  • A. UL
    UL is the vehicle registration code used on license plates for the city of Ulm in Germany.
  • B. UL
    UL is the two-letter IATA airline designator assigned to SriLankan Airlines, the flag carrier of Sri Lanka.
  • C. UL
    UL is the New York Stock Exchange ticker symbol for Unilever, a major multinational consumer goods company known for its food, personal care, and household products.
  • D. LU
    LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
  • E. LU
    LU is the vehicle registration code for the German city of Ludwigshafen am Rhein in the state of Rhineland-Palatinate.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: vehicleRegistrationCodeDistrict
Context triple: [Lauterach, vehicleRegistrationCodeDistrict, UL]
  • A. identifiesRegistrationDistrict
    Indicates that one entity specifies or designates the registration district to which another entity belongs or is associated.
  • B. districtCode chosen
    Indicates that an entity is associated with, or identified by, a specific administrative district code.
  • C. vehicleRegistrationCode
    Indicates the official registration identifier assigned to a vehicle, typically used for legal identification and record-keeping.
  • D. vehicleRegistrationAuthority
    Indicates the authority or organization responsible for officially registering a vehicle and maintaining its registration records.
  • E. governmentDistrict
    Indicates that a government entity has jurisdiction over or is administratively associated with a specific district.
  • F. None of above.

Provenance (6 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_69ca83ec8db08190a9110df8232885d2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda7903208190b4e29a1591aab78a completed April 1, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0779de5a88190b6a9266c976e05b1 completed April 4, 2026, 2:29 a.m.
NEDg Description generation batch_69d0782d305481909a2b41615e890863 completed April 4, 2026, 2:32 a.m.
NED2 Entity disambiguation (via description) batch_69d0789ef4288190bf4d52e7ed47bd9b completed April 4, 2026, 2:34 a.m.
PD Predicate disambiguation batch_69cc7a3daeb481908b0abde3fbc1f1f0 completed April 1, 2026, 1:51 a.m.
Created at: March 30, 2026, 7:28 p.m.