Triple

T9528644
Position Surface form Disambiguated ID Type / Status
Subject Mary Darnall E229825 entity
Predicate residence P75 FINISHED
Object Maryland E707 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: Maryland | Statement: [Mary Darnall, residence, Maryland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maryland
Context triple: [Mary Darnall, residence, Maryland]
  • A. Maryland chosen
    Maryland is a Mid-Atlantic U.S. state known for its Chesapeake Bay shoreline, colonial history, and proximity to the nation’s capital.
  • B. Maryland
    Maryland is a small village in Otsego County, New York, known primarily as a rural residential community in the central part of the state.
  • C. Maryland and Delaware
    Maryland and Delaware are two neighboring Mid-Atlantic U.S. states on the East Coast, known respectively for the Chesapeake Bay and the city of Baltimore, and for its Atlantic beaches and role as the nation’s first state to ratify the Constitution.
  • D. Virginia
    Virginia is a small community located within the town of Georgina in Ontario, Canada.
  • E. Virginia
    Virginia is a coastal township in Montserrado County, Liberia, known for its beaches and proximity to the capital, Monrovia.
  • 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_69ca8479934c81908006d0e6e970ae05 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98b1b93481909812245ac14e4988 completed April 1, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1527253588190ac365203ef382a2d completed April 4, 2026, 6:03 p.m.
Created at: March 30, 2026, 8 p.m.