Triple

T4718733
Position Surface form Disambiguated ID Type / Status
Subject Gisborne E104710 entity
Predicate namedAfter P63 FINISHED
Object William Gisborne
William Gisborne was a 19th-century New Zealand politician and public administrator who served as Colonial Secretary and played a key role in the development of the colony’s government.
 E471378 NE FINISHED

How this triple was built (4 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: William Gisborne | Statement: [Gisborne, namedAfter, William Gisborne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: William Gisborne
Context triple: [Gisborne, namedAfter, William Gisborne]
  • A. James Sansbury
    James Sansbury is a technology entrepreneur best known as a co-founder of the software company Altera.
  • B. James G. Smyth
    James G. Smyth was a mountaineer known for making the first recorded ascent of Mont Blanc du Tacul in the Alps.
  • C. Thomas Burke
    Thomas Burke was an American sprinter who became the first Olympic champion in both the 100-meter and 400-meter races at the modern Games.
  • D. Thomas Burke
    Thomas Burke was an American politician who served as the third Governor of North Carolina during the early years of the United States.
  • E. Thomas Burke
    Thomas Burke was a British author best known for his early 20th-century stories set in London’s East End, including the tale that inspired the film "Broken Blossoms."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: William Gisborne
Triple: [Gisborne, namedAfter, William Gisborne]
Generated description
William Gisborne was a 19th-century New Zealand politician and public administrator who served as Colonial Secretary and played a key role in the development of the colony’s government.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: William Gisborne
Target entity description: William Gisborne was a 19th-century New Zealand politician and public administrator who served as Colonial Secretary and played a key role in the development of the colony’s government.
  • A. James Sansbury
    James Sansbury is a technology entrepreneur best known as a co-founder of the software company Altera.
  • B. James G. Smyth
    James G. Smyth was a mountaineer known for making the first recorded ascent of Mont Blanc du Tacul in the Alps.
  • C. Thomas Burke
    Thomas Burke was an American sprinter who became the first Olympic champion in both the 100-meter and 400-meter races at the modern Games.
  • D. Thomas Burke
    Thomas Burke was an American politician who served as the third Governor of North Carolina during the early years of the United States.
  • E. Thomas Burke
    Thomas Burke was a British author best known for his early 20th-century stories set in London’s East End, including the tale that inspired the film "Broken Blossoms."
  • F. None of above. chosen

Provenance (5 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd642779a08190b01e588d515cf498 completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4d7f0bc88190b2e5a2d6cfd16892 completed March 21, 2026, 7:49 a.m.
NEDg Description generation batch_69be4e1891408190adc09699d0347cbd completed March 21, 2026, 7:51 a.m.
NED2 Entity disambiguation (via description) batch_69be4ef501e081908a75547e9bb52c0c completed March 21, 2026, 7:55 a.m.
Created at: March 20, 2026, 1:18 p.m.