Triple

T8569670
Position Surface form Disambiguated ID Type / Status
Subject Lincoln Kirstein E202895 entity
Predicate givenName P17 FINISHED
Object Lincoln E346042 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: Lincoln | Statement: [Lincoln Kirstein, givenName, Lincoln]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lincoln
Context triple: [Lincoln Kirstein, givenName, Lincoln]
  • A. Lincoln
    Lincoln is a luxury automobile marque of the Ford Motor Company known for its premium sedans and SUVs.
  • B. Lincoln chosen
    Lincoln is a masculine given name of English origin most famously associated with U.S. President Abraham Lincoln.
  • C. Lincoln
    Lincoln is a common English surname most famously associated with U.S. President Abraham Lincoln and his family.
  • D. Lincoln
    Lincoln is a 2012 historical drama film directed by Steven Spielberg that focuses on U.S. President Abraham Lincoln’s efforts to pass the Thirteenth Amendment abolishing slavery.
  • E. Lincoln
    Lincoln is a historic American city in Illinois best known as the namesake of President Abraham Lincoln and for its rich Civil War–era heritage.
  • 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_69ca8327b0a881908606ff860713964d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbea4091f48190b5174d7a5cfd2bd8 completed March 31, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebb8e8b9481908f7096acefaa0ffd completed April 2, 2026, 6:55 p.m.
Created at: March 30, 2026, 6:21 p.m.