Triple

T4008597
Position Surface form Disambiguated ID Type / Status
Subject Philadelphia city line E90586 entity
Predicate separates P1175 FINISHED
Object Norwood, Pennsylvania E378192 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: Norwood, Pennsylvania | Statement: [Philadelphia city line, separates, Norwood, Pennsylvania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norwood, Pennsylvania
Context triple: [Philadelphia city line, separates, Norwood, Pennsylvania]
  • A. Norwood, Pennsylvania chosen
    Norwood, Pennsylvania is a small suburban borough near Philadelphia known for its residential neighborhoods and local parks.
  • B. Havertown, Pennsylvania
    Havertown, Pennsylvania is a suburban community west of Philadelphia known for its residential neighborhoods, strong public schools, and historic Irish-American roots.
  • C. Springfield, Pennsylvania
    Springfield, Pennsylvania is a township in Delaware County best known as the birthplace of renowned 18th-century painter Benjamin West.
  • D. Hanover, Pennsylvania
    Hanover, Pennsylvania is a small borough in York County known for its snack food industry and historic role in the Civil War.
  • E. Bridgeport, Pennsylvania
    Bridgeport, Pennsylvania is a small borough in Montgomery County, near major commercial and transportation hubs in the Philadelphia metropolitan area.
  • 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_69aed95e44088190aff7d90a151b1b20 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa647f80819081180eb267f1cfcc completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b6371762c08190ab0b829777e62540 completed March 15, 2026, 4:35 a.m.
Created at: March 9, 2026, 3:34 p.m.