Triple

T8532081
Position Surface form Disambiguated ID Type / Status
Subject Neunkirchen E201976 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object NK
NK is the vehicle registration code used on license plates for the Neunkirchen district in Germany.
 E740193 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: NK | Statement: [Neunkirchen, vehicleRegistrationCode, NK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NK
Context triple: [Neunkirchen, vehicleRegistrationCode, NK]
  • A. NK
    NK is the two-letter IATA airline designator assigned to Spirit Airlines, a U.S.-based ultra-low-cost carrier.
  • B. KN
    KN is the IATA airline designator assigned to China United Airlines, a Chinese domestic carrier based in Beijing.
  • C. NKo
    NKo is a Unicode block that encodes the characters of the N’Ko script used for writing several West African Mande languages.
  • D. N
    The N is a New York City Subway service that runs along the Broadway Line in Manhattan and connects Queens, Manhattan, and Brooklyn.
  • E. Ng
    Ng is a common Chinese surname found across various Chinese-speaking communities and the diaspora, often representing the Cantonese or Hokkien romanization of the character 吳 (Wu).
  • 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: NK
Triple: [Neunkirchen, vehicleRegistrationCode, NK]
Generated description
NK is the vehicle registration code used on license plates for the Neunkirchen district in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NK
Target entity description: NK is the vehicle registration code used on license plates for the Neunkirchen district in Germany.
  • A. NK
    NK is the two-letter IATA airline designator assigned to Spirit Airlines, a U.S.-based ultra-low-cost carrier.
  • B. KN
    KN is the IATA airline designator assigned to China United Airlines, a Chinese domestic carrier based in Beijing.
  • C. NKo
    NKo is a Unicode block that encodes the characters of the N’Ko script used for writing several West African Mande languages.
  • D. N
    The N is a New York City Subway service that runs along the Broadway Line in Manhattan and connects Queens, Manhattan, and Brooklyn.
  • E. Ng
    Ng is a common Chinese surname found across various Chinese-speaking communities and the diaspora, often representing the Cantonese or Hokkien romanization of the character 吳 (Wu).
  • 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_69ca832355b08190b8b6a4ab4a4a3554 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe676e2ac8190b65a3d2a935776fd completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d70f81881908ac784608ad7a2aa completed April 2, 2026, 1:21 p.m.
NEDg Description generation batch_69ce6e69213c8190add7eb9cc74b1a33 completed April 2, 2026, 1:26 p.m.
NED2 Entity disambiguation (via description) batch_69ce6f28ae6481909a8a13613f3eb5e0 completed April 2, 2026, 1:29 p.m.
Created at: March 30, 2026, 6:17 p.m.