Triple

T10972171
Position Surface form Disambiguated ID Type / Status
Subject Shawn Hatosy E259267 entity
Predicate familyName P18 FINISHED
Object Hatosy
Hatosy is the surname of American actor and director Shawn Hatosy, known for his roles in film and television dramas.
 E897536 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: Hatosy | Statement: [Shawn Hatosy, familyName, Hatosy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hatosy
Context triple: [Shawn Hatosy, familyName, Hatosy]
  • A. Maromokotro
    Maromokotro is the tallest mountain in Madagascar, located in the island’s northern highlands.
  • B. Anjara
    Anjara is a town in northern Jordan situated within the hilly, forested region of Ajloun, known for its Christian pilgrimage sites and scenic landscapes.
  • C. Rahaita
    Rahaita is a settlement located in Eritrea's Southern Red Sea Region, along the country's arid Red Sea coastal area.
  • D. Mahafaly Malagasy
    Mahafaly Malagasy is a regional variety of the Malagasy language spoken primarily by the Mahafaly people in southwestern Madagascar.
  • E. Antsirabe
    Antsirabe is a highland city in central Madagascar known for its cool climate, thermal springs, and colonial-era architecture.
  • 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: Hatosy
Triple: [Shawn Hatosy, familyName, Hatosy]
Generated description
Hatosy is the surname of American actor and director Shawn Hatosy, known for his roles in film and television dramas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hatosy
Target entity description: Hatosy is the surname of American actor and director Shawn Hatosy, known for his roles in film and television dramas.
  • A. Maromokotro
    Maromokotro is the tallest mountain in Madagascar, located in the island’s northern highlands.
  • B. Anjara
    Anjara is a town in northern Jordan situated within the hilly, forested region of Ajloun, known for its Christian pilgrimage sites and scenic landscapes.
  • C. Rahaita
    Rahaita is a settlement located in Eritrea's Southern Red Sea Region, along the country's arid Red Sea coastal area.
  • D. Mahafaly Malagasy
    Mahafaly Malagasy is a regional variety of the Malagasy language spoken primarily by the Mahafaly people in southwestern Madagascar.
  • E. Antsirabe
    Antsirabe is a highland city in central Madagascar known for its cool climate, thermal springs, and colonial-era architecture.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7719b5edc81908c1019f81e78bd2e completed April 9, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d7a0b3dc819084fbda3227caf5b5 completed April 18, 2026, 1 a.m.
NEDg Description generation batch_69e2ff1ffb8c8190ba97f3c2e3c8c601 completed April 18, 2026, 3:48 a.m.
NED2 Entity disambiguation (via description) batch_69e3261cc4f48190ba0e5645f37cd4b5 completed April 18, 2026, 6:35 a.m.
Created at: April 8, 2026, 9:24 p.m.