Triple

T23095056
Position Surface form Disambiguated ID Type / Status
Subject Alexander Meiklejohn E575860 entity
Predicate workLocation P7 FINISHED
Object Madison, Wisconsin 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: Madison, Wisconsin | Statement: [Alexander Meiklejohn, workLocation, Madison, Wisconsin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madison, Wisconsin
Context triple: [Alexander Meiklejohn, workLocation, Madison, Wisconsin]
  • A. Madison, Wisconsin, United States chosen
    Madison, Wisconsin, United States is the capital city of Wisconsin, known for its major research university, vibrant cultural scene, and numerous lakes.
  • B. Washington, Wisconsin
    Washington, Wisconsin is a small town located in Eau Claire County in the western part of the U.S. state of Wisconsin.
  • C. Madison
    Madison is a suburban city in northern Alabama known for its proximity to Huntsville and its strong schools and residential communities.
  • D. Madison
    Madison is a coastal town in south-central Connecticut known for its beaches, historic New England charm, and popular Hammonasset Beach State Park.
  • E. Madison
    Madison is the codename for a later-generation Itanium processor variant developed by Intel for high-end server and enterprise computing.
  • 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_69e245c060b48190a9bd61a47a16db17 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18de3b2b481909ef598b447ed4dd2 completed April 29, 2026, 4:49 a.m.
Created at: April 17, 2026, 3:57 p.m.