Triple

T3800618
Position Surface form Disambiguated ID Type / Status
Subject Colonel Alexander Bliss E91677 entity
Predicate associatedWith P37 FINISHED
Object Abraham Lincoln E268 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: Abraham Lincoln | Statement: [Colonel Alexander Bliss, associatedWith, Abraham Lincoln]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abraham Lincoln
Context triple: [Colonel Alexander Bliss, associatedWith, Abraham Lincoln]
  • A. Abraham Lincoln chosen
    Abraham Lincoln was the 16th president of the United States, best known for leading the country through the Civil War and issuing the Emancipation Proclamation that began the process of ending slavery.
  • B. 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.
  • C. Lincoln
    Lincoln is a luxury automobile marque of the Ford Motor Company known for its premium sedans and SUVs.
  • D. Lincoln
    Lincoln is a masculine given name of English origin most famously associated with U.S. President Abraham Lincoln.
  • E. Lincoln
    Lincoln is a suburban town in eastern Massachusetts known for its conservation land, historic sites, and commuter access to Boston.
  • 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_69aed96354f48190a768966d6bd19b04 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee7b82c0c81909519c3988b108d8b completed March 9, 2026, 3:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51211a34c8190a3cd8d45e8f7dd87 completed March 14, 2026, 7:45 a.m.
Created at: March 9, 2026, 3:15 p.m.