Triple

T15276131
Position Surface form Disambiguated ID Type / Status
Subject Carolina E365144 entity
Predicate hasMasculineForm P15475 FINISHED
Object Charles E13673 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: Charles | Statement: [Carolina, hasMasculineForm, Charles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charles
Context triple: [Carolina, hasMasculineForm, Charles]
  • A. Charles chosen
    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.
  • B. 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.
  • C. Charles Robert
    Charles Robert, better known as Charles I of Hungary, was a 14th-century Angevin king who restored royal authority and initiated economic and administrative reforms in medieval Hungary.
  • D. George
    George is the given name of George W. McLaurin, the first African American student admitted to the University of Oklahoma.
  • E. George
    George is the given name of John Stewart-Murray, the 8th Duke of Atholl, a Scottish peer and soldier of the late 19th and early 20th centuries.
  • 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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00952731c8190bf6a5e6e10c95b94 completed April 15, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fef895f9708190a44ee7ade1c46a7d completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:14 a.m.