Triple

T13379607
Position Surface form Disambiguated ID Type / Status
Subject Lycoming County E319278 entity
Predicate hasLargestCity P235 FINISHED
Object Williamsport E81809 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: Williamsport | Statement: [Lycoming County, hasLargestCity, Williamsport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Williamsport
Context triple: [Lycoming County, hasLargestCity, Williamsport]
  • A. Williamsport, Pennsylvania chosen
    Williamsport, Pennsylvania is a city in north-central Pennsylvania best known as the birthplace of Little League Baseball and host of the annual Little League World Series.
  • B. Wilkes-Barre
    Wilkes-Barre is a small city in northeastern Pennsylvania known for its location along the Susquehanna River and its historical ties to coal mining and industry.
  • C. Altoona
    Altoona is a small suburban city in central Iowa known for its proximity to Des Moines and attractions like the Adventureland amusement park and Prairie Meadows casino and racetrack.
  • D. Altoona
    Altoona is a small town located in Etowah County in the state of Alabama, United States.
  • E. Mattersburg
    Mattersburg is a small Austrian town that serves as an important local center in the eastern state of Burgenland.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadce56c6c8190adf4e19f6d1bc233 completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7397f098c8190a2062d8c1a74d28f completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:33 p.m.