Triple

T1355749
Position Surface form Disambiguated ID Type / Status
Subject Albert Hackett E28983 entity
Predicate familyName P18 FINISHED
Object Hackett
Hackett is a surname of English and Irish origin borne by various notable individuals across fields such as literature, sports, and entertainment.
 E156676 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: Hackett | Statement: [Albert Hackett, familyName, Hackett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hackett
Context triple: [Albert Hackett, familyName, Hackett]
  • A. Hackett
    Hackett is the middle name of David H. Souter, a former Associate Justice of the United States Supreme Court.
  • B. Harrington
    Harrington is a small coastal town in New South Wales, Australia, known for its beaches, fishing, and proximity to the Manning River and Crowdy Bay National Park.
  • C. Hucknall
    Hucknall is a market town in Nottinghamshire, England, historically known for its coal mining industry and as the burial place of the poet Lord Byron.
  • D. Harbison
    Harbison is a surname most notably associated with American composer John Harbison, known for his contributions to contemporary classical music.
  • E. Banagher
    Banagher is a small Irish town in County Offaly known for its historic bridge over the River Shannon and its traditional boating and angling activities.
  • 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: Hackett
Triple: [Albert Hackett, familyName, Hackett]
Generated description
Hackett is a surname of English and Irish origin borne by various notable individuals across fields such as literature, sports, and entertainment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hackett
Target entity description: Hackett is a surname of English and Irish origin borne by various notable individuals across fields such as literature, sports, and entertainment.
  • A. Hackett
    Hackett is the middle name of David H. Souter, a former Associate Justice of the United States Supreme Court.
  • B. Harrington
    Harrington is a small coastal town in New South Wales, Australia, known for its beaches, fishing, and proximity to the Manning River and Crowdy Bay National Park.
  • C. Hucknall
    Hucknall is a market town in Nottinghamshire, England, historically known for its coal mining industry and as the burial place of the poet Lord Byron.
  • D. Harbison
    Harbison is a surname most notably associated with American composer John Harbison, known for his contributions to contemporary classical music.
  • E. Banagher
    Banagher is a small Irish town in County Offaly known for its historic bridge over the River Shannon and its traditional boating and angling activities.
  • 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_69a498571d248190a0ac9eb02d97097f completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c28c8dd0819082f94c9e7c837c5f completed March 1, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce6e264481909f7cb907486d3e08 completed March 8, 2026, 1:18 a.m.
NEDg Description generation batch_69accf141c3481909ae5ea849aee7604 completed March 8, 2026, 1:21 a.m.
NED2 Entity disambiguation (via description) batch_69accfb8acfc8190bba379d8bb114c29 completed March 8, 2026, 1:24 a.m.
Created at: March 1, 2026, 7:56 p.m.