Triple

T10789555
Position Surface form Disambiguated ID Type / Status
Subject U.S. Route 62 E254540 entity
Predicate passesThroughCity P416 FINISHED
Object Sharon, Pennsylvania E502519 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: Sharon, Pennsylvania | Statement: [U.S. Route 62, passesThroughCity, Sharon, Pennsylvania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sharon, Pennsylvania
Context triple: [U.S. Route 62, passesThroughCity, Sharon, Pennsylvania]
  • A. Sharon, Pennsylvania chosen
    Sharon, Pennsylvania is a small industrial city in Mercer County known historically for steel manufacturing and its location near the Ohio border in western Pennsylvania.
  • B. Sharon Hill, Pennsylvania
    Sharon Hill, Pennsylvania is a small suburban borough located just southwest of Philadelphia in Delaware County.
  • C. Shillington, Pennsylvania
    Shillington, Pennsylvania is a small borough in Berks County that functions largely as a residential suburb of nearby Reading.
  • D. Pulaski, Pennsylvania
    Pulaski, Pennsylvania is a small unincorporated community in Lawrence County known for its rural character within western Pennsylvania.
  • E. Parkside, Pennsylvania
    Parkside, Pennsylvania is a small residential borough located in Delaware County, just outside Philadelphia.
  • 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d732f4b1388190a1364e56a90e8388 completed April 9, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69de84ddd6f48190a11eae9233d3ef9f completed April 14, 2026, 6:18 p.m.
Created at: April 8, 2026, 9:17 p.m.