Triple

T8945537
Position Surface form Disambiguated ID Type / Status
Subject Luke, Maryland E213211 entity
Predicate borderWith P224 FINISHED
Object West Virginia E24143 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: West Virginia | Statement: [Luke, Maryland, borderWith, West Virginia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: West Virginia
Context triple: [Luke, Maryland, borderWith, West Virginia]
  • A. West Virginia chosen
    West Virginia is a landlocked, mountainous U.S. state in the Appalachian region, known for its coal mining history, outdoor recreation, and distinct cultural heritage.
  • B. WV
    WV is the postcode area covering Wolverhampton and surrounding parts of the West Midlands in England.
  • C. Virginia
    Virginia is a small community located within the town of Georgina in Ontario, Canada.
  • D. Virginia
    Virginia is a coastal township in Montserrado County, Liberia, known for its beaches and proximity to the capital, Monrovia.
  • E. Virginia
    Virginia is a U.S. state in the Mid-Atlantic and Southeastern regions, known for its pivotal role in American history, including being home to several early presidents and key Revolutionary and Civil War sites.
  • 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_69ca839843408190a39069a029a89f15 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66db998c8190999a7a686bbdda1f completed April 1, 2026, 12:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd099b2f48190b81d6747bad4b992 completed April 3, 2026, 2:37 p.m.
Created at: March 30, 2026, 6:59 p.m.