Triple

T16213085
Position Surface form Disambiguated ID Type / Status
Subject Canton, Massachusetts E393514 entity
Predicate namedAfter P63 FINISHED
Object Canton, China E242593 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, China | Statement: [Canton, Massachusetts, namedAfter, Canton, China]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canton, China
Context triple: [Canton, Massachusetts, namedAfter, Canton, China]
  • A. Canton, China chosen
    Canton, China is the former English name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • B. Hsiangcheng, China
    Hsiangcheng, China is a town in Henan Province known as the birthplace of author and social critic Os Guinness.
  • C. City of Canton
    The City of Canton is a local municipal government that administers public services and infrastructure, including the Canton Municipal Airport, for its community.
  • D. Hangtou
    Hangtou is a town in Shanghai, China, known as the southern terminus of the Shanghai Metro’s Line 18.
  • E. Caizhou
    Caizhou was a historic Chinese city best known as the final capital of the Jurchen-led Jin dynasty before its fall to the Mongols.
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e227f2c1288190bfaed49c364bfa22 completed April 17, 2026, 12:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0007932f088190b6c20913cfb932f4 completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 5:03 a.m.