Triple

T8930408
Position Surface form Disambiguated ID Type / Status
Subject VOW E212637 entity
Predicate hasRelatedTicker P45350 FINISHED
Object VWAGY
VWAGY is the U.S. over-the-counter (OTC) American Depositary Receipt representing shares of German automaker Volkswagen AG.
 E37751 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: VWAGY | Statement: [VOW, hasRelatedTicker, VWAGY]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VWAGY
Context triple: [VOW, hasRelatedTicker, VWAGY]
  • A. VWAG
    VWAG is the stock ticker symbol under which the multinational automotive manufacturer Volkswagen Group is publicly traded.
  • B. VIAG
    VIAG is the ICAO airport code for Agra Airport, a public and military airfield serving the city of Agra in Uttar Pradesh, India.
  • C. G-VWOW
    G-VWOW is a Boeing 747-400 aircraft that formerly flew for Virgin Atlantic and was later converted into the "Cosmic Girl" carrier plane for Virgin Orbit’s air-launched orbital rockets.
  • D. Vomag
    Vomag was a German vehicle manufacturer best known for producing military trucks and armored vehicles, including variants of the Panzer IV, during the World War II era.
  • E. Vagn
    Vagn is a Scandinavian given name, historically used in Denmark and other Nordic countries.
  • 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: VWAGY
Triple: [VOW, hasRelatedTicker, VWAGY]
Generated description
VWAGY is the U.S. over-the-counter (OTC) American Depositary Receipt representing shares of German automaker Volkswagen AG.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VWAGY
Target entity description: VWAGY is the U.S. over-the-counter (OTC) American Depositary Receipt representing shares of German automaker Volkswagen AG.
  • A. VWAG chosen
    VWAG is the stock ticker symbol under which the multinational automotive manufacturer Volkswagen Group is publicly traded.
  • B. VIAG
    VIAG is the ICAO airport code for Agra Airport, a public and military airfield serving the city of Agra in Uttar Pradesh, India.
  • C. G-VWOW
    G-VWOW is a Boeing 747-400 aircraft that formerly flew for Virgin Atlantic and was later converted into the "Cosmic Girl" carrier plane for Virgin Orbit’s air-launched orbital rockets.
  • D. Vomag
    Vomag was a German vehicle manufacturer best known for producing military trucks and armored vehicles, including variants of the Panzer IV, during the World War II era.
  • E. Vagn
    Vagn is a Scandinavian given name, historically used in Denmark and other Nordic countries.
  • F. None of above.

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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6676d5d881908ce78cbb5561a68b completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba63544081909394500f28b34ccb completed April 3, 2026, 1:02 p.m.
NEDg Description generation batch_69cfbc685bf08190a716a28cc9bcd031 completed April 3, 2026, 1:11 p.m.
NED2 Entity disambiguation (via description) batch_69cfbcc19ee081909e564040fea2ad9a completed April 3, 2026, 1:12 p.m.
Created at: March 30, 2026, 6:57 p.m.