Triple

T10986578
Position Surface form Disambiguated ID Type / Status
Subject Maple Shade Township E259644 entity
Predicate suburbanOf P15376 FINISHED
Object Philadelphia 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 | Statement: [Maple Shade Township, suburbanOf, Philadelphia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philadelphia
Context triple: [Maple Shade Township, suburbanOf, Philadelphia]
  • A. Philadelphia
    Philadelphia is a small town located in Loudon County, Tennessee, known for its rural character and historic Southern charm.
  • B. 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.
  • C. Philadelphia
    Philadelphia was the ancient Greco-Roman name of the city now known as Amman, the capital of Jordan.
  • D. 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.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d787b2e4a88190a81504eee77e2298 completed April 9, 2026, 11:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3c80ada908190a244eccc2b48df60 completed April 18, 2026, 6:06 p.m.
Created at: April 8, 2026, 9:24 p.m.