Triple

T91159
Position Surface form Disambiguated ID Type / Status
Subject George II of Great Britain E1831 entity
Predicate givenName P17 FINISHED
Object George E22107 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: George | Statement: [George II of Great Britain, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [George II of Great Britain, givenName, George]
  • A. George chosen
    George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
  • B. Henry
    Henry is the given name of Henry A. Kissinger, the influential American diplomat and political scientist who served as U.S. Secretary of State and National Security Advisor.
  • C. Edward
    Edward is a masculine given name of English origin, historically associated with kings of England and notable figures such as U.S. Senator Edward M. Kennedy.
  • D. Charles
    Charles is a masculine given name of Germanic origin that has been widely used across Europe and the English-speaking world, borne by numerous historical figures, royalty, and notable individuals.
  • E. Thomas
    Thomas is the given name of Thomas Malthus, the influential English economist and demographer known for his theories on population growth and resource limits.
  • 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_69a24d1a97dc819094e6c021fe9b05a7 completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24f6c29888190890caa7872d63ac6 completed Feb. 28, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69a352712e808190a7595a67591de73a completed Feb. 28, 2026, 8:39 p.m.
Created at: Feb. 28, 2026, 2:07 a.m.