Triple

T4357858
Position Surface form Disambiguated ID Type / Status
Subject Ferdinand Walsin Esterhazy E98593 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 Walsin Esterhazy, givenName, Ferdinand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ferdinand
Context triple: [Ferdinand Walsin Esterhazy, 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. Fernando
    "Fernando" is a popular 1976 ballad by Swedish pop group ABBA, known for its nostalgic, storytelling lyrics and melodic harmonies.
  • D. 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.
  • E. Fernando
    Fernando is a masculine given name of Spanish and Portuguese origin, commonly used in many Spanish-speaking and Lusophone 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351c7fa1881908bdc844a7142eb65 completed March 12, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e501671c8190bf8a9998f46a9f3b completed March 14, 2026, 10:45 p.m.
Created at: March 12, 2026, 11:16 p.m.