Triple

T7127448
Position Surface form Disambiguated ID Type / Status
Subject Wyoming Valley E166099 entity
Predicate containsCity P294 FINISHED
Object Larksville E481157 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: Larksville | Statement: [Wyoming Valley, containsCity, Larksville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Larksville
Context triple: [Wyoming Valley, containsCity, Larksville]
  • A. Larksville chosen
    Larksville is a small borough in northeastern Pennsylvania, United States, situated within the Wyoming Valley near the city of Wilkes-Barre.
  • B. Slatersville
    Slatersville is a historic village in North Smithfield, Rhode Island, known as one of America’s first planned mill villages centered around early textile manufacturing.
  • C. Yatesville
    Yatesville is a small town located in the U.S. state of Georgia.
  • D. Robertstown
    Robertstown is a small Irish village in County Kildare known for its historic canal-side setting and heritage as a former inland waterways hub.
  • E. Millerton
    Millerton is a small hamlet and village in Dutchess County, New York, known for its rural charm and proximity to the Taconic State Park and the Harlem Valley.
  • 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_69c6888350588190870cd552b427a1cd completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e64ee8ac81909ee1c7cb1db3af33 completed March 27, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ad8d00848190a5a4b9b64b3426e7 completed March 28, 2026, 10:29 a.m.
Created at: March 27, 2026, 2:44 p.m.