Triple

T21309068
Position Surface form Disambiguated ID Type / Status
Subject Prince Gustav of Denmark E525280 entity
Predicate givenName P17 FINISHED
Object Gustav E140654 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: Gustav | Statement: [Prince Gustav of Denmark, givenName, Gustav]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gustav
Context triple: [Prince Gustav of Denmark, givenName, Gustav]
  • A. Gustav chosen
    Gustav is a masculine given name of German origin, borne by several notable historical figures including scientists, artists, and royalty.
  • B. Gustaf
    Gustaf is the given name of Carl Gustaf Emil Mannerheim, the Finnish military leader and statesman who served as Commander-in-Chief during World War II and later as President of Finland.
  • C. Wilhelm
    Wilhelm is a Germanic given name, equivalent to William, historically borne by numerous European nobles, rulers, and notable figures.
  • D. Ludwig
    Ludwig is a masculine given name of Germanic origin, historically associated with nobility and rulers and used in various forms across many European languages.
  • E. Ludwig
    Ludwig is a 1973 historical drama film by Italian director Luchino Visconti that portrays the life and tragic decline of Bavaria’s King Ludwig II.
  • 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_69e0b518b8948190ad69cf9a8784d397 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e75aa916548190a11f8bb4255e3fed completed April 21, 2026, 11:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09b4122eb48190bcfccba3e1b2e9c3 completed May 17, 2026, 12:26 p.m.
Created at: April 16, 2026, 4:06 p.m.