Triple

T12038746
Position Surface form Disambiguated ID Type / Status
Subject Francis Dayle Hearn E286606 entity
Predicate familyName P18 FINISHED
Object Hearn
Hearn is a surname of English and Irish origin borne by various notable individuals across fields such as sports, entertainment, and literature.
 E961469 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: Hearn | Statement: [Francis Dayle Hearn, familyName, Hearn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hearn
Context triple: [Francis Dayle Hearn, familyName, Hearn]
  • A. Haren
    Haren is a village in the Netherlands that functions as a submunicipality within the municipality of Oss in the province of North Brabant.
  • B. Haren
    Haren is a district in the northern part of Brussels, Belgium, known for its mix of residential areas, industrial zones, and transport infrastructure.
  • C. Herlihy
    Herlihy is an Irish-origin surname borne by various notable individuals, including writers, scholars, and public figures.
  • D. Hendrie
    Hendrie is a given name and surname, primarily of Scottish origin, that functions as a variant form of the name Henry.
  • E. Rennahan
    Rennahan is a surname most notably associated with Ray Rennahan, an American cinematographer known for his pioneering work with Technicolor.
  • 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: Hearn
Triple: [Francis Dayle Hearn, familyName, Hearn]
Generated description
Hearn is a surname of English and Irish origin borne by various notable individuals across fields such as sports, entertainment, and literature.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hearn
Target entity description: Hearn is a surname of English and Irish origin borne by various notable individuals across fields such as sports, entertainment, and literature.
  • A. Haren
    Haren is a village in the Netherlands that functions as a submunicipality within the municipality of Oss in the province of North Brabant.
  • B. Haren
    Haren is a district in the northern part of Brussels, Belgium, known for its mix of residential areas, industrial zones, and transport infrastructure.
  • C. Herlihy
    Herlihy is an Irish-origin surname borne by various notable individuals, including writers, scholars, and public figures.
  • D. Hendrie
    Hendrie is a given name and surname, primarily of Scottish origin, that functions as a variant form of the name Henry.
  • E. Rennahan
    Rennahan is a surname most notably associated with Ray Rennahan, an American cinematographer known for his pioneering work with Technicolor.
  • 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_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040a8be881908f4841145a7b4e86 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d8a9af881909e28783b0d83ed82 completed May 1, 2026, 12:33 p.m.
NEDg Description generation batch_69f53d930714819080f92d223d930389 completed May 1, 2026, 11:56 p.m.
NED2 Entity disambiguation (via description) batch_69f564b826ec819098906cf735e45093 completed May 2, 2026, 2:43 a.m.
Created at: April 8, 2026, 9:47 p.m.