Triple

T7789067
Position Surface form Disambiguated ID Type / Status
Subject Arthur Johnson E187327 entity
Predicate workLocation P7 FINISHED
Object Philadelphia, Pennsylvania E171 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: Philadelphia, Pennsylvania | Statement: [Arthur Johnson, workLocation, Philadelphia, Pennsylvania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philadelphia, Pennsylvania
Context triple: [Arthur Johnson, workLocation, Philadelphia, Pennsylvania]
  • A. Philadelphia
    Philadelphia is a small town located in Loudon County, Tennessee, known for its rural character and historic Southern charm.
  • B. Philadelphia chosen
    Philadelphia is a major historic U.S. city in Pennsylvania known for its role in the American Revolution, iconic landmarks like Independence Hall and the Liberty Bell, and its rich cultural and academic institutions.
  • C. Philadelphia
    Philadelphia is a 1993 American legal drama film that broke ground in mainstream cinema for its portrayal of HIV/AIDS, homophobia, and discrimination in the workplace.
  • D. Philadelphia
    Philadelphia was the ancient Greco-Roman name of the city now known as Amman, the capital of Jordan.
  • E. Filadelfia
    Filadelfia is a small municipality and town located in the Caldas Department of Colombia, known for its coffee-growing economy in the Andean region.
  • 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_69ca82af2d2c8190963861f5e0b8bf21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cae7e8a0d08190b6d4ca560681eb35 completed March 30, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb59f230d48190ad4cb08e9e73f19e completed March 31, 2026, 5:21 a.m.
Created at: March 30, 2026, 4:25 p.m.