Triple

T3152012
Position Surface form Disambiguated ID Type / Status
Subject Ferdinand Schörner E65897 entity
Predicate givenName P17 FINISHED
Object Ferdinand E60224 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: Ferdinand | Statement: [Ferdinand Schörner, givenName, Ferdinand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ferdinand
Context triple: [Ferdinand Schörner, givenName, Ferdinand]
  • A. Ferdinand chosen
    Ferdinand is a masculine given name of Germanic origin historically borne by numerous European nobles and monarchs.
  • B. Fernando
    "Fernando" is a popular 1976 ballad by Swedish pop group ABBA, known for its nostalgic, storytelling lyrics and melodic harmonies.
  • C. Fernando
    Fernando is the given name of Salgueiro Maia, a key Portuguese military officer who played a leading role in the Carnation Revolution.
  • D. Alfonso
    Alfonso is a masculine given name of Spanish and Italian origin historically borne by numerous kings, nobles, and notable figures across Europe.
  • E. Leopoldo
    Leopoldo is a masculine given name of Spanish and Italian origin, commonly used in Latin American and European countries.
  • 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_69ad8584485081909ed529e890cadc4a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada5c27258819099c46a657779780b completed March 8, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b235bf4a008190ba6264103a9d67b7 completed March 12, 2026, 3:40 a.m.
Created at: March 8, 2026, 3:05 p.m.