Triple

T991306
Position Surface form Disambiguated ID Type / Status
Subject Anif E21395 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object SL
SL is the vehicle registration code used for the Austrian municipality of Anif in the state of Salzburg.
 E117326 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: SL | Statement: [Anif, hasVehicleRegistrationCode, SL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SL
Context triple: [Anif, hasVehicleRegistrationCode, SL]
  • A. SL
    The Mercedes-Benz SL is a long-running line of luxury grand touring roadsters renowned for combining high performance with elegant design and advanced technology.
  • B. SL
    SL is the public transport authority and brand responsible for operating and coordinating the mass transit system in the Stockholm region of Sweden.
  • C. LS
    LS is the IATA airline designator used by the British low-cost carrier Jet2.com.
  • D. Sal
    Sal is a popular Cape Verdean island known for its white-sand beaches, year-round sunshine, and vibrant seaside resorts centered around the town of Santa Maria.
  • E. SV
    SV is the two-letter ISO 3166-1 alpha-2 country code assigned to El Salvador.
  • 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: SL
Triple: [Anif, hasVehicleRegistrationCode, SL]
Generated description
SL is the vehicle registration code used for the Austrian municipality of Anif in the state of Salzburg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SL
Target entity description: SL is the vehicle registration code used for the Austrian municipality of Anif in the state of Salzburg.
  • A. SL
    The Mercedes-Benz SL is a long-running line of luxury grand touring roadsters renowned for combining high performance with elegant design and advanced technology.
  • B. SL
    SL is the public transport authority and brand responsible for operating and coordinating the mass transit system in the Stockholm region of Sweden.
  • C. LS
    LS is the IATA airline designator used by the British low-cost carrier Jet2.com.
  • D. Sal
    Sal is a popular Cape Verdean island known for its white-sand beaches, year-round sunshine, and vibrant seaside resorts centered around the town of Santa Maria.
  • E. SV
    SV is the two-letter ISO 3166-1 alpha-2 country code assigned to El Salvador.
  • 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_69a493c383dc8190a03257f22d4b4183 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4c25e5081909ff1ada6b8bf617a completed March 1, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac258f823c8190afeff79b6a4df911 completed March 7, 2026, 1:18 p.m.
NEDg Description generation batch_69ac261af46c81908d61b29ea97c0884 completed March 7, 2026, 1:20 p.m.
NED2 Entity disambiguation (via description) batch_69ac26ee09f0819098a7b1adcbb79053 completed March 7, 2026, 1:23 p.m.
Created at: March 1, 2026, 7:41 p.m.