Triple

T5152164
Position Surface form Disambiguated ID Type / Status
Subject Emmanuel Léopold Guillaume François Marie E116220 entity
Predicate givenName P17 FINISHED
Object Emmanuel E147057 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: Emmanuel | Statement: [Emmanuel Léopold Guillaume François Marie, givenName, Emmanuel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emmanuel
Context triple: [Emmanuel Léopold Guillaume François Marie, givenName, Emmanuel]
  • A. Emmanuel
    Emmanuel is a Belgian prince, a member of the royal family of Belgium and the son of King Philippe and Queen Mathilde.
  • B. Emmanuel chosen
    Emmanuel is a masculine given name of Hebrew origin meaning "God is with us," used in various languages and cultures.
  • C. Immanuel
    Immanuel is the given name of the influential German philosopher Immanuel Kant, a central figure in modern Western philosophy.
  • D. Emanuel
    Emanuel is a surname most prominently associated with Rahm Emanuel, the American politician and former mayor of Chicago.
  • E. Simeon
    Simeon is a biblical figure, one of the twelve sons of Jacob and a progenitor of one of the tribes of Israel.
  • 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_69bd445d94788190b72e2cc563120995 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd78daab708190a42734a14dddb2fc completed March 20, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed0099afc8190badca81bd5efb8f6 completed March 21, 2026, 5:06 p.m.
Created at: March 20, 2026, 1:44 p.m.