Triple

T5336458
Position Surface form Disambiguated ID Type / Status
Subject Västerhaninge station E123837 entity
Predicate hasStationCode P1289 FINISHED
Object Vhg
Vhg is the station code used to identify Västerhaninge railway station in Sweden’s public transport system.
 E511392 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: Vhg | Statement: [Västerhaninge station, hasStationCode, Vhg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vhg
Context triple: [Västerhaninge station, hasStationCode, Vhg]
  • A. GVG
    GVG is the standard abbreviation for the German Courts Constitution Act, a key statute that regulates the structure and jurisdiction of the ordinary courts in Germany.
  • B. VBG
    VBG is the abbreviated name of the German association of botanical gardens, Verband Botanischer Gärten e.V.
  • C. HVF
    HVF is a data-focused startup and innovation lab created by entrepreneur Max Levchin to explore and build companies around large-scale data problems.
  • D. VOG
    VOG is the IATA airport code for Volgograd International Airport, a regional air transport hub serving the city of Volgograd in Russia.
  • E. Vuhovi
    Vuhovi is a locality in the Democratic Republic of the Congo known for being heavily affected during the 2018–2020 Kivu Ebola epidemic.
  • 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: Vhg
Triple: [Västerhaninge station, hasStationCode, Vhg]
Generated description
Vhg is the station code used to identify Västerhaninge railway station in Sweden’s public transport system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vhg
Target entity description: Vhg is the station code used to identify Västerhaninge railway station in Sweden’s public transport system.
  • A. GVG
    GVG is the standard abbreviation for the German Courts Constitution Act, a key statute that regulates the structure and jurisdiction of the ordinary courts in Germany.
  • B. VBG
    VBG is the abbreviated name of the German association of botanical gardens, Verband Botanischer Gärten e.V.
  • C. HVF
    HVF is a data-focused startup and innovation lab created by entrepreneur Max Levchin to explore and build companies around large-scale data problems.
  • D. VOG
    VOG is the IATA airport code for Volgograd International Airport, a regional air transport hub serving the city of Volgograd in Russia.
  • E. Vuhovi
    Vuhovi is a locality in the Democratic Republic of the Congo known for being heavily affected during the 2018–2020 Kivu Ebola epidemic.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85b104c081908b81236a0142e1c8 completed March 20, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf18c1e1f88190a47489a9491eaf08 completed March 21, 2026, 10:16 p.m.
NEDg Description generation batch_69bf199394e08190948f70a9884a39b6 completed March 21, 2026, 10:20 p.m.
NED2 Entity disambiguation (via description) batch_69bf19f186bc81908e378f61100417a9 completed March 21, 2026, 10:21 p.m.
Created at: March 20, 2026, 2 p.m.