Triple

T9351259
Position Surface form Disambiguated ID Type / Status
Subject Fort McHenry Tunnel E225022 entity
Predicate connects P390 FINISHED
Object Canton E395819 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: Canton | Statement: [Fort McHenry Tunnel, connects, Canton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canton
Context triple: [Fort McHenry Tunnel, connects, Canton]
  • A. Canton
    Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • B. Canton
    Canton is a small New England town in Hartford County, Connecticut, known for its historic village centers and scenic Farmington River setting.
  • C. Canton chosen
    Canton is a historic waterfront neighborhood in southeast Baltimore, Maryland, known for its revitalized harborfront, rowhouses, and vibrant bar and restaurant scene.
  • D. Canton
    Canton is a city in northeastern Ohio best known as the home of the Pro Football Hall of Fame.
  • E. Canton
    Canton is a suburban town in Norfolk County, Massachusetts, located southwest of Boston and known for its residential character and local historic sites.
  • 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_69ca842abfd48190949d71c3b86eeba8 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4f9248c08190a7bb40feec2eb217 completed April 1, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e445c5308190be122215c92fd03d completed April 4, 2026, 10:13 a.m.
Created at: March 30, 2026, 7:41 p.m.