Triple

T894651
Position Surface form Disambiguated ID Type / Status
Subject Edward Rutledge E19316 entity
Predicate givenName P17 FINISHED
Object Edward E5488 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: Edward | Statement: [Edward Rutledge, givenName, Edward]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edward
Context triple: [Edward Rutledge, givenName, Edward]
  • A. Edward chosen
    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.
  • B. Richard
    Richard is a common masculine given name of Germanic origin, widely used in English-speaking countries.
  • C. George
    George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
  • D. George
    George is a town in South Africa’s Western Cape province, known as a gateway to the Garden Route and for its scenic mountains and forests.
  • E. 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.
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad22b6fc819093e655c8ce1f738b completed March 1, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69af5ca0ede48190b2c45761a3f92517 completed March 9, 2026, 11:49 p.m.
Created at: March 1, 2026, 7:39 p.m.