Triple

T17585211
Position Surface form Disambiguated ID Type / Status
Subject Panther Affair E428303 entity
Predicate hasParticipant P149 FINISHED
Object SMS Panther NE NERFINISHED

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: SMS Panther | Statement: [Panther Affair, hasParticipant, SMS Panther]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SMS Panther
Context triple: [Panther Affair, hasParticipant, SMS Panther]
  • A. SMS Panther chosen
    SMS Panther was a German gunboat whose 1911 deployment to the Moroccan port of Agadir helped trigger the Second Moroccan Crisis and heighten pre–World War I tensions among European powers.
  • B. SMS Pommern
    SMS Pommern was a pre-dreadnought battleship of the German Imperial Navy that served in World War I and was sunk at the Battle of Jutland in 1916.
  • C. SMS König
    SMS König was a German Kaiser-class battleship that served as the lead ship of her class in the Imperial German Navy during World War I, notably participating in the Battle of Jutland.
  • D. SMS Gazelle
    SMS Gazelle was a 19th-century Prussian naval warship that served as an important vessel in the development and operations of the Prussian Navy.
  • E. SIM
    SIM is the vehicle registration code used on license plates for vehicles registered in the Simmern region of Germany.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e463d113b08190975506f3558c1eca completed April 19, 2026, 5:10 a.m.
Created at: April 10, 2026, 5:50 a.m.