Triple

T1045661
Position Surface form Disambiguated ID Type / Status
Subject Gerswalde E22571 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object UM
UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
 E120686 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: UM | Statement: [Gerswalde, vehicleRegistrationCode, UM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UM
Context triple: [Gerswalde, vehicleRegistrationCode, UM]
  • A. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • 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 vehicle registration code used on license plates for the city of Ulm in Germany.
  • D. UB
    UB was the common abbreviation for the Urząd Bezpieczeństwa, the communist-era Polish secret police and security service notorious for political repression after World War II.
  • E. UC
    UC is a leading Chilean university, widely recognized for its academic excellence and strong influence in education, research, and public policy in Latin America.
  • 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: UM
Triple: [Gerswalde, vehicleRegistrationCode, UM]
Generated description
UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UM
Target entity description: UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • A. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • 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 vehicle registration code used on license plates for the city of Ulm in Germany.
  • D. UB
    UB was the common abbreviation for the Urząd Bezpieczeństwa, the communist-era Polish secret police and security service notorious for political repression after World War II.
  • E. UC
    UC is a leading Chilean university, widely recognized for its academic excellence and strong influence in education, research, and public policy in Latin America.
  • 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_69a493d91478819094cc01fb65564bc1 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b84bb0048190badf6d2f7f684d99 completed March 1, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bc97dec81909b6ad48e3f203923 completed March 7, 2026, 2:52 p.m.
NEDg Description generation batch_69ac3c42c2c081909ccadbf944d3aa6c completed March 7, 2026, 2:54 p.m.
NED2 Entity disambiguation (via description) batch_69ac3cbd43848190854add440753fdad completed March 7, 2026, 2:57 p.m.
Created at: March 1, 2026, 7:42 p.m.