Triple

T14507881
Position Surface form Disambiguated ID Type / Status
Subject Becca E340311 entity
Predicate homeLocation P75 FINISHED
Object Pennsylvania 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: Pennsylvania | Statement: [Becca, homeLocation, Pennsylvania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pennsylvania
Context triple: [Becca, homeLocation, Pennsylvania]
  • 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. Pensilvania
    Pensilvania is a municipality and town located in the Caldas Department of Colombia, known for its coffee-growing economy and mountainous Andean landscape.
  • C. Pennsylvania and New Jersey
    Pennsylvania and New Jersey are neighboring U.S. states in the Mid-Atlantic region, separated for much of their length by the Delaware River.
  • D. Penn
    Penn is a picturesque village in Buckinghamshire, England, known for its historic church, traditional Chilterns architecture, and scenic countryside setting.
  • E. Penn
    Penn is the stage and given name of Penn Jillette, the outspoken magician, comedian, and half of the famed duo Penn & Teller.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de94e40e44819084f323f8f9982b75 completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a39d55c8190bbc7b76fab6b8b39 completed May 8, 2026, 5:52 a.m.
Created at: April 10, 2026, 1:21 a.m.