Triple

T9434050
Position Surface form Disambiguated ID Type / Status
Subject Ferdinand III, Grand Duke of Tuscany E227456 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 III, Grand Duke of Tuscany, givenName, Ferdinand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ferdinand
Context triple: [Ferdinand III, Grand Duke of Tuscany, givenName, 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 was the given name of the Duke of Alba who served as governor-general, a prominent Spanish noble and military leader.
  • 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_69ca8437a7ac81908651de48f2d2141d completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7e62d53c81908055e0967e6cd54d completed April 1, 2026, 8:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1104514d481908d7cb9a87a01f1e2 completed April 4, 2026, 1:21 p.m.
Created at: March 30, 2026, 7:49 p.m.