Triple

T14304889
Position Surface form Disambiguated ID Type / Status
Subject HMS Cornwallis E354668 entity
Predicate locationDuringEvent P373 FINISHED
Object Nanking E29741 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: Nanking | Statement: [HMS Cornwallis, locationDuringEvent, Nanking]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanking
Context triple: [HMS Cornwallis, locationDuringEvent, Nanking]
  • A. Nanjing chosen
    Nanjing is a major city in eastern China, historically significant as a former national capital and cultural center, and now an important political, economic, and educational hub on the Yangtze River.
  • B. Chungking
    Chungking (now commonly spelled Chongqing) is a major city in southwest China that served as the wartime capital during the Second Sino-Japanese War and World War II.
  • C. Nankou
    Nankou is a town in Beijing’s Changping District known as a key gateway area near the Juyongguan section of the Great Wall.
  • D. Dajing
    Dajing is a Chinese given name notably borne by Olympic short track speed skating champion Wu Dajing.
  • E. Hangtou
    Hangtou is a town in Shanghai, China, known as the southern terminus of the Shanghai Metro’s Line 18.
  • 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85afabe48190926d6098047f4bcf completed April 14, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d2a56a4819095b5c2164b1ad9fb completed May 8, 2026, 1:32 a.m.
Created at: April 10, 2026, 1:12 a.m.