Triple

T17252425
Position Surface form Disambiguated ID Type / Status
Subject Nordostbahnhof station E418788 entity
Predicate hasStationCode P1289 FINISHED
Object NNO
NNO is the station code for Nordostbahnhof, a railway station in Nuremberg, Germany.
 E1259058 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: NNO | Statement: [Nordostbahnhof station, hasStationCode, NNO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NNO
Context triple: [Nordostbahnhof station, hasStationCode, NNO]
  • A. NNU
    NNU is a comprehensive public university in Nanjing, China, known for its strong programs in teacher education, humanities, and sciences.
  • B. NNS
    NNS is the commonly used abbreviation for Newport News Shipbuilding, a major American shipyard known for constructing U.S. Navy aircraft carriers and submarines.
  • C. ONN
    ONN is the acronym for Cuba’s National Office of Standardization, the state body responsible for developing and overseeing national standards and quality regulations.
  • D. NNSY
    NNSY is a major United States Navy shipyard and maintenance facility located in Norfolk, Virginia.
  • E. NOB
    NOB is the abbreviation for the Schweizerische Nordostbahn, a former Swiss railway company that operated in northeastern Switzerland in the 19th and early 20th centuries.
  • 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: NNO
Triple: [Nordostbahnhof station, hasStationCode, NNO]
Generated description
NNO is the station code for Nordostbahnhof, a railway station in Nuremberg, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NNO
Target entity description: NNO is the station code for Nordostbahnhof, a railway station in Nuremberg, Germany.
  • A. NNU
    NNU is a comprehensive public university in Nanjing, China, known for its strong programs in teacher education, humanities, and sciences.
  • B. NNS
    NNS is the commonly used abbreviation for Newport News Shipbuilding, a major American shipyard known for constructing U.S. Navy aircraft carriers and submarines.
  • C. ONN
    ONN is the acronym for Cuba’s National Office of Standardization, the state body responsible for developing and overseeing national standards and quality regulations.
  • D. NNSY
    NNSY is a major United States Navy shipyard and maintenance facility located in Norfolk, Virginia.
  • E. NOB
    NOB is the abbreviation for Dutch National Opera & Ballet, the leading institution for opera and ballet performances in the Netherlands.
  • 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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e6a1b648190a8bb2deb67bbdfdc completed April 19, 2026, 1:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170fb89248190ae431ce51dfeaffd completed May 11, 2026, 6:02 a.m.
NEDg Description generation batch_6a017258cb9c8190baa828104d30fdbf completed May 11, 2026, 6:08 a.m.
NED2 Entity disambiguation (via description) batch_6a017620d2d8819099292be7bc4db4df completed May 11, 2026, 6:24 a.m.
Created at: April 10, 2026, 5:39 a.m.