Triple

T14402931
Position Surface form Disambiguated ID Type / Status
Subject HMS Bounty E357114 entity
Predicate captainRank P31052 FINISHED
Object Lieutenant William Bligh E223342 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: Lieutenant William Bligh | Statement: [HMS Bounty, captainRank, Lieutenant William Bligh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lieutenant William Bligh
Context triple: [HMS Bounty, captainRank, Lieutenant William Bligh]
  • A. William Bligh chosen
    William Bligh was a British naval officer and navigator best known as the captain during the infamous mutiny on the HMS Bounty.
  • B. Bligh
    Bligh is the middle name of Malcolm Turnbull, the 29th Prime Minister of Australia.
  • C. James H. Cook
    James H. Cook was a 19th-century rancher and fossil collector whose discoveries and collaborations with paleontologists were central to the significance of the Agate Fossil Beds area.
  • D. Woodes Rogers
    Woodes Rogers was an English sea captain and privateer who became famous for his circumnavigation of the globe and later served as the first royal governor of the Bahamas, where he worked to suppress piracy.
  • E. Captain Johnson
    Captain Johnson is a fictional character from the 1978 equestrian drama film "International Velvet."
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90860ae481908e175decda8624d5 completed April 14, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bc424f88190ab3a1c1aec61cb40 completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:17 a.m.