Triple

T9413987
Position Surface form Disambiguated ID Type / Status
Subject district of Rosenheim E226767 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object RO
RO is the vehicle registration code used on license plates for vehicles registered in the district of Rosenheim in Germany.
E797519 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: RO | Statement: [district of Rosenheim, hasVehicleRegistrationCode, RO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RO
Context triple: [district of Rosenheim, hasVehicleRegistrationCode, RO]
  • A. RO
    RO is the IATA airline designator assigned to TAROM, the flag carrier airline of Romania.
  • B. RO
    RO is the vehicle registration code used on license plates for vehicles registered in the Province of Rovigo in Italy.
  • C. RO
    RO is the stock ticker symbol for Roche, the multinational Swiss healthcare and pharmaceutical company.
  • D. RON
    RON is the official currency code for the Romanian leu used in international finance and currency exchange.
  • E. ROL
    ROL was the former ISO 4217 currency code for the old Romanian leu used before the 2005 currency redenomination in Romania.
  • 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: RO
Triple: [district of Rosenheim, hasVehicleRegistrationCode, RO]
Generated description
RO is the vehicle registration code used on license plates for vehicles registered in the district of Rosenheim in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: RO
Target entity description: RO is the vehicle registration code used on license plates for vehicles registered in the district of Rosenheim in Germany.
  • A. RO
    RO is the IATA airline designator assigned to TAROM, the flag carrier airline of Romania.
  • B. RO
    RO is the stock ticker symbol for Roche, the multinational Swiss healthcare and pharmaceutical company.
  • C. RO
    RO is the vehicle registration code used on license plates for vehicles registered in the Province of Rovigo in Italy.
  • D. RON
    RON is the official currency code for the Romanian leu used in international finance and currency exchange.
  • E. ROL
    ROL was the former ISO 4217 currency code for the old Romanian leu used before the 2005 currency redenomination in Romania.
  • 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_69ca843280488190bc65600e843ef9e6 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd68c680e48190be82e3829e8711f0 completed April 1, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d107b63cf48190a072e3434a7b85a8 completed April 4, 2026, 12:44 p.m.
NEDg Description generation batch_69d108466fb481909682fcaac354b312 completed April 4, 2026, 12:47 p.m.
NED2 Entity disambiguation (via description) batch_69d108be82888190b0ec08119cd00b68 completed April 4, 2026, 12:49 p.m.
Created at: March 30, 2026, 7:47 p.m.