Triple

T21381455
Position Surface form Disambiguated ID Type / Status
Subject Newark-on-Trent E527365 entity
Predicate hasNearbyTown P3883 FINISHED
Object Lincoln NE NERFINISHED

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: [Newark-on-Trent, hasNearbyTown, Lincoln]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lincoln
Context triple: [Newark-on-Trent, hasNearbyTown, 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 historic cathedral city in the East Midlands of England, renowned for its medieval architecture, including Lincoln Cathedral and Lincoln Castle.
  • C. Lincoln
    Lincoln is a suburban town in Providence County, Rhode Island, known for its historic mill villages, residential neighborhoods, and recreational areas such as Lincoln Woods State Park.
  • 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 small city in Talladega County, Alabama, known for its proximity to the Talladega Superspeedway and Logan Martin Lake.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51f363c8190944000ab5523b02b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0cf89f08190bd7c0d552232d948 completed April 22, 2026, 11:28 a.m.
Created at: April 16, 2026, 5:11 p.m.