Triple

T5623637
Position Surface form Disambiguated ID Type / Status
Subject 4th United States Congress E147667 entity
Predicate location P40 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: [4th United States Congress, location, Philadelphia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philadelphia
Context triple: [4th United States Congress, location, 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_69c00906f2a88190a992c66b13d606d4 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02214b4948190b71a9f59499092f6 completed March 22, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097c480cc8190a42001a4c0b065a2 completed March 23, 2026, 1:30 a.m.
Created at: March 22, 2026, 3:40 p.m.