Triple

T8190891
Position Surface form Disambiguated ID Type / Status
Subject Weil am Rhein E191300 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object LÖ
LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
 E718250 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: LÖ | Statement: [Weil am Rhein, vehicleRegistrationCode, LÖ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LÖ
Context triple: [Weil am Rhein, vehicleRegistrationCode, LÖ]
  • A. Lo
    Lo is a dialect of the Lo-Toga language spoken on the Torres Islands in northern Vanuatu.
  • B. Lom
    Lom is a mountainous municipality in Innlandet county, Norway, known for its historic stave church and as a gateway to the Jotunheimen National Park.
  • C. Lyov
    Lyov is a transliterated form of the Russian given name Lev, commonly associated with figures like the writer Leo (Lev) Tolstoy.
  • D. LOU
    LOU is the standard sports abbreviation used to represent the Louisville Panthers team.
  • E. LLOY
    LLOY is the London Stock Exchange ticker symbol for Lloyds Banking Group, a major British financial services and banking institution.
  • 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: LÖ
Triple: [Weil am Rhein, vehicleRegistrationCode, LÖ]
Generated description
LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LÖ
Target entity description: LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • A. Lo
    Lo is a dialect of the Lo-Toga language spoken on the Torres Islands in northern Vanuatu.
  • B. Lom
    Lom is a mountainous municipality in Innlandet county, Norway, known for its historic stave church and as a gateway to the Jotunheimen National Park.
  • C. Lyov
    Lyov is a transliterated form of the Russian given name Lev, commonly associated with figures like the writer Leo (Lev) Tolstoy.
  • D. LOU
    LOU is the standard sports abbreviation used to represent the Louisville Panthers team.
  • E. LLOY
    LLOY is the London Stock Exchange ticker symbol for Lloyds Banking Group, a major British financial services and banking institution.
  • 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_69ca82c5b6948190a583c096fb0a6c71 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4da2f4108190b9b69cb7f41ef374 completed March 31, 2026, 4:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cced979d408190851088c6d3f4df24 completed April 1, 2026, 10:04 a.m.
NEDg Description generation batch_69ccf1b5f95481909fdb08d00d06023e completed April 1, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_69cd059457788190a900402ee4cd50d5 completed April 1, 2026, 11:46 a.m.
Created at: March 30, 2026, 5:41 p.m.