Triple

T2212369
Position Surface form Disambiguated ID Type / Status
Subject Panzer IV E50946 entity
Predicate manufacturer P490 FINISHED
Object 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.
 E245727 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: Vomag | Statement: [Panzer IV, manufacturer, Vomag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vomag
Context triple: [Panzer IV, manufacturer, Vomag]
  • A. Volm
    The Volm are an advanced alien species in the TV series "Falling Skies" who arrive on Earth as potential allies to humanity in its war against the Espheni invaders.
  • B. Vestli
    Vestli is a residential neighborhood in the Stovner borough of Oslo, Norway, known for being served by the Oslo Metro.
  • C. Mvezo
    Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
  • D. Vekoma
    Vekoma is a Dutch roller coaster and amusement ride manufacturer known worldwide for designing and building a wide range of thrill and family attractions for theme parks.
  • E. Veltro
    Veltro is the nickname of the Macchi C.205, an Italian World War II fighter aircraft renowned for its speed and agility.
  • 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: Vomag
Triple: [Panzer IV, manufacturer, Vomag]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vomag
Target entity description: 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.
  • A. Volm
    The Volm are an advanced alien species in the TV series "Falling Skies" who arrive on Earth as potential allies to humanity in its war against the Espheni invaders.
  • B. Vestli
    Vestli is a residential neighborhood in the Stovner borough of Oslo, Norway, known for being served by the Oslo Metro.
  • C. Mvezo
    Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
  • D. Vekoma
    Vekoma is a Dutch roller coaster and amusement ride manufacturer known worldwide for designing and building a wide range of thrill and family attractions for theme parks.
  • E. Veltro
    Veltro is the nickname of the Macchi C.205, an Italian World War II fighter aircraft renowned for its speed and agility.
  • 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_69a88b06709c8190978fb2418470d1b6 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfecea6c8190b762bbfda8490e31 completed March 7, 2026, 6:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae655245c48190a37f4b6344a9a3dc completed March 9, 2026, 6:14 a.m.
NEDg Description generation batch_69ae66579c008190876ce89581337293 completed March 9, 2026, 6:19 a.m.
NED2 Entity disambiguation (via description) batch_69ae668ef8bc819085ed1c83f447d396 completed March 9, 2026, 6:19 a.m.
Created at: March 4, 2026, 7:46 p.m.