Triple

T10472690
Position Surface form Disambiguated ID Type / Status
Subject William S. Harney E246966 entity
Predicate familyName P18 FINISHED
Object Harney
Harney is a surname of Irish origin borne by various notable individuals, including military figures and public officials.
E864639 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: Harney | Statement: [William S. Harney, familyName, Harney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harney
Context triple: [William S. Harney, familyName, Harney]
  • A. Kicking Horse Coffee
    Kicking Horse Coffee is a Canadian coffee company known for its organic, fair-trade whole-bean coffees and bold branding.
  • B. Peet
    Peet is a surname most notably associated with American actress Amanda Peet.
  • C. Kensett
    Kensett is the surname of John Frederick Kensett, a prominent 19th-century American landscape painter associated with the Hudson River School.
  • D. Columbia Crest
    Columbia Crest is the highest summit of Mount Rainier, forming the true geographic peak of this iconic stratovolcano in Washington State.
  • E. Brewster
    Brewster is a small hamlet and census-designated place in Putnam County, New York, known for its historic downtown and role as a local commercial and transportation hub.
  • 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: Harney
Triple: [William S. Harney, familyName, Harney]
Generated description
Harney is a surname of Irish origin borne by various notable individuals, including military figures and public officials.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Harney
Target entity description: Harney is a surname of Irish origin borne by various notable individuals, including military figures and public officials.
  • A. Kicking Horse Coffee
    Kicking Horse Coffee is a Canadian coffee company known for its organic, fair-trade whole-bean coffees and bold branding.
  • B. Peet
    Peet is a surname most notably associated with American actress Amanda Peet.
  • C. Kensett
    Kensett is the surname of John Frederick Kensett, a prominent 19th-century American landscape painter associated with the Hudson River School.
  • D. Columbia Crest
    Columbia Crest is the highest summit of Mount Rainier, forming the true geographic peak of this iconic stratovolcano in Washington State.
  • E. Brewster
    Brewster is a small hamlet and census-designated place in Putnam County, New York, known for its historic downtown and role as a local commercial and transportation hub.
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5094daac081908e0ba5e10c1bbb67 completed April 7, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8a0140f4c81908ce95b28e09cb04b completed April 10, 2026, 7 a.m.
NEDg Description generation batch_69d8a166404881909c28141fefea2936 completed April 10, 2026, 7:06 a.m.
NED2 Entity disambiguation (via description) batch_69d8a2c550ac81908444c6abfe14698a completed April 10, 2026, 7:12 a.m.
Created at: April 6, 2026, 12:20 p.m.