Triple

T11821099
Position Surface form Disambiguated ID Type / Status
Subject Michael Best (law firm) E281129 entity
Predicate hasOfficeLocation P1268 FINISHED
Object Madison, Wisconsin E11896 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: Madison, Wisconsin | Statement: [Michael Best (law firm), hasOfficeLocation, Madison, Wisconsin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madison, Wisconsin
Context triple: [Michael Best (law firm), hasOfficeLocation, 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. Madison
    Madison is a suburban city in northern Alabama known for its proximity to Huntsville and its strong schools and residential communities.
  • C. Madison
    Madison is a coastal town in south-central Connecticut known for its beaches, historic New England charm, and popular Hammonasset Beach State Park.
  • D. Madison
    Madison is the codename for a later-generation Itanium processor variant developed by Intel for high-end server and enterprise computing.
  • E. Madison
    Madison is a small town that serves as one of the local communities within Madison County.
  • 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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5e87e488190905bc3bb6d721e56 completed April 10, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69f43f9e99788190a5a8abb135426038 completed May 1, 2026, 5:52 a.m.
Created at: April 8, 2026, 9:42 p.m.