Triple

T11074167
Position Surface form Disambiguated ID Type / Status
Subject Derry, Pennsylvania E261822 entity
Predicate hasRegionCode P3446 FINISHED
Object US-PA E13698 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: US-PA | Statement: [Derry, Pennsylvania, hasRegionCode, US-PA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: US-PA
Context triple: [Derry, Pennsylvania, hasRegionCode, US-PA]
  • A. Pennsylvania chosen
    Pennsylvania is a historically significant U.S. state in the Mid-Atlantic and Northeastern regions, known for cities like Philadelphia and Pittsburgh and its central role in the nation’s founding.
  • B. Penn
    Penn is a private Ivy League research university in Philadelphia known for its strong programs in business, law, medicine, and the liberal arts.
  • C. Penn
    Penn is the stage and given name of Penn Jillette, the outspoken magician, comedian, and half of the famed duo Penn & Teller.
  • D. Penn
    Penn is a 2006 Tamil-language romantic comedy film directed by A. Venkatesh and produced by AVM Productions.
  • E. US-MS
    US-MS is the ISO 3166-2 code representing the U.S. state of Mississippi.
  • 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7994e32fc8190a6591d9e82b68f75 completed April 9, 2026, 12:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c8cc77988190aad54f56dbd0f8cf completed April 18, 2026, 6:09 p.m.
Created at: April 8, 2026, 9:26 p.m.