Triple

T14690895
Position Surface form Disambiguated ID Type / Status
Subject Full fathom five E345028 entity
Predicate hasCharacterMention P5716 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: [Full fathom five, hasCharacterMention, Ferdinand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ferdinand
Context triple: [Full fathom five, hasCharacterMention, Ferdinand]
  • A. Ferdinand chosen
    Ferdinand is a masculine given name of Germanic origin historically borne by numerous European nobles and monarchs.
  • B. Ferdinand
    Ferdinand is a 2017 computer-animated family film about a gentle bull who prefers flowers to fighting, produced by Blue Sky Studios and released by 20th Century Fox.
  • C. Ferdinande
    Ferdinande is the given name of Archduchess Auguste Ferdinande of Austria, a 19th-century member of the Habsburg-Lorraine dynasty.
  • D. Fernando
    "Fernando" is a popular 1976 ballad by Swedish pop group ABBA, known for its nostalgic, storytelling lyrics and melodic harmonies.
  • E. Fernando
    Fernando is the given name of Fernando Primo de Rivera, a 19th-century Spanish general and politician who briefly served as Prime Minister of Spain.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb585d46c81908d6964130914cec4 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cde041081908ae2f2c75a9d5eb2 completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:28 a.m.