Triple

T18244740
Position Surface form Disambiguated ID Type / Status
Subject Langensalza E436920 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object UH
UH is the German vehicle registration code assigned to the Unstrut-Hainich district, which includes the town of Bad Langensalza in Thuringia.
 E1313364 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: UH | Statement: [Langensalza, hasVehicleRegistrationCode, UH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UH
Context triple: [Langensalza, hasVehicleRegistrationCode, UH]
  • A. UH
    UH is the commonly used abbreviation for the University of Helsinki, a major research university in Finland.
  • B. UH
    UH is a major public research university located in Houston, Texas, known for its diverse student body and strong programs in fields such as engineering, business, and the arts.
  • C. UW
    UW is a leading Canadian public research university known for its strong engineering, computer science, and co-operative education programs.
  • D. UW
    UW is a common abbreviation for the University of Wisconsin, whose athletic teams are known as the Wisconsin Badgers.
  • E. UW
    UW is the commonly used abbreviation for the University of Warsaw, a major public research university in Poland’s capital city.
  • 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: UH
Triple: [Langensalza, hasVehicleRegistrationCode, UH]
Generated description
UH is the German vehicle registration code assigned to the Unstrut-Hainich district, which includes the town of Bad Langensalza in Thuringia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UH
Target entity description: UH is the German vehicle registration code assigned to the Unstrut-Hainich district, which includes the town of Bad Langensalza in Thuringia.
  • A. UH
    UH is the commonly used abbreviation for the University of Helsinki, a major research university in Finland.
  • B. UH
    UH is a major public research university located in Houston, Texas, known for its diverse student body and strong programs in fields such as engineering, business, and the arts.
  • C. UW
    UW is a leading Canadian public research university known for its strong engineering, computer science, and co-operative education programs.
  • D. UW
    UW is a common abbreviation for the University of Wisconsin, whose athletic teams are known as the Wisconsin Badgers.
  • E. UW
    UW is the commonly used abbreviation for the University of Warsaw, a major public research university in Poland’s capital city.
  • 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_69d8b91104e08190a8241f7d260a5162 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4f7e5d63081908d0e6249578867a1 completed April 19, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03ac733e708190a7fde1fb61db5d5f completed May 12, 2026, 10:40 p.m.
NEDg Description generation batch_6a03ad2be6e0819081426da968a57db0 completed May 12, 2026, 10:43 p.m.
NED2 Entity disambiguation (via description) batch_6a03ad8898748190b57028bb2e2ed207 completed May 12, 2026, 10:45 p.m.
Created at: April 10, 2026, 10:33 a.m.