Triple

T6188480
Position Surface form Disambiguated ID Type / Status
Subject Molly Parker E138123 entity
Predicate notableWork P4 FINISHED
Object Madison E303595 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 | Statement: [Molly Parker, notableWork, Madison]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madison
Context triple: [Molly Parker, notableWork, Madison]
  • A. Madison
    Madison is a common English surname and given name, historically associated with U.S. President James Madison and now widely used as a first name, especially for girls.
  • B. Madison
    Madison is the capital city of Wisconsin, known for its lakes, vibrant university community, and progressive culture.
  • 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 chosen
    Madison is a coastal town in south-central Connecticut known for its beaches, historic New England charm, and popular Hammonasset Beach State Park.
  • E. Racine
    Racine is a city in southeastern Wisconsin located on the shore of Lake Michigan, known historically for its manufacturing industry and Danish kringle pastries.
  • 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_69c008a8fd408190b7ec6e42934974a6 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062192c5481909eb41f8c5d1208a3 completed March 22, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f06c770819087e055cfe6c8b134 completed March 23, 2026, 4:49 p.m.
Created at: March 22, 2026, 4:19 p.m.