Triple

T6872507
Position Surface form Disambiguated ID Type / Status
Subject Allegheny College E158584 entity
Predicate city P40 FINISHED
Object Meadville E524738 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: Meadville | Statement: [Allegheny College, city, Meadville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meadville
Context triple: [Allegheny College, city, Meadville]
  • A. Meadville chosen
    Meadville is a small city in northwestern Pennsylvania known historically as an early center of industry and home to Allegheny College.
  • B. Mattersburg
    Mattersburg is a small Austrian town that serves as an important local center in the eastern state of Burgenland.
  • C. Wellsboro
    Wellsboro is a small historic borough in north-central Pennsylvania known for its charming gas-lit streets and proximity to the Pennsylvania Grand Canyon.
  • D. Knittelfeld
    Knittelfeld is a small town in the Austrian state of Styria known for its industrial heritage and proximity to the Red Bull Ring motor racing circuit.
  • E. Brownsville, Pennsylvania
    Brownsville, Pennsylvania is a historic borough along the Monongahela River known for its early role in American westward expansion and riverboat commerce.
  • 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_69c68832af1481908ce356e133ebaebe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8c73ea08190b6bb1463e7ead47b completed March 27, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c769ee07308190abfd1d59ecb4db21 completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:22 p.m.