Triple

T16217041
Position Surface form Disambiguated ID Type / Status
Subject Krupp armor E393619 entity
Predicate developedBy P73 FINISHED
Object Krupp E31323 NE FINISHED

How this triple was built (2 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: Krupp | Statement: [Krupp armor, developedBy, Krupp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krupp
Context triple: [Krupp armor, developedBy, Krupp]
  • A. Krupp (company) chosen
    Krupp (company) was a major German industrial conglomerate best known for its steel production and armaments manufacturing, playing a central role in both World Wars and in the development of heavy industry in Germany.
  • B. Deutsche Werke AG
    Deutsche Werke AG was a German state-owned industrial and shipbuilding company, notably active in naval construction during the early to mid-20th century.
  • C. Borsigwerke
    Borsigwerke is a Berlin U-Bahn station on line U6 serving the Tegel district in the city’s northwest.
  • D. Deutsche Eisenwerke
    Deutsche Eisenwerke was a German industrial firm known for producing military equipment, including armored vehicles, during the World War II era.
  • E. Deutsche Werft AG
    Deutsche Werft AG was a German shipbuilding company based in Hamburg, known for constructing naval vessels and submarines, particularly during the World War II era.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e227f76f748190831d230d32c18611 completed April 17, 2026, 12:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000796bc5c81909d2acb68851c9bb8 completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 5:03 a.m.