Triple

T15190863
Position Surface form Disambiguated ID Type / Status
Subject Never Back Down E363005 entity
Predicate writer P1360 FINISHED
Object Chris Hauty
Chris Hauty is an American screenwriter and novelist best known for his work on action films and political thrillers.
E1141866 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: Chris Hauty | Statement: [Never Back Down, writer, Chris Hauty]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chris Hauty
Context triple: [Never Back Down, writer, Chris Hauty]
  • A. Michael A. Helfant
    Michael A. Helfant is a film producer and entertainment executive known for his work on genre and thriller projects, including the 2013 crime thriller "The Call."
  • B. Larry Stenger
    Larry Stenger is one of the original founders associated with the early formation of semiconductor company Advanced Micro Devices (AMD).
  • C. Craig A. Stough
    Craig A. Stough is an American local government leader who serves as the mayor of Sylvania, Ohio.
  • D. Michael Goulian
    Michael Goulian is an American aerobatic champion and airshow performer best known for competing at the highest level in international air racing events.
  • E. Mark P. McCahill
    Mark P. McCahill is an American computer scientist best known for pioneering early internet technologies, including creating the Gopher protocol for distributed document search and retrieval.
  • 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: Chris Hauty
Triple: [Never Back Down, writer, Chris Hauty]
Generated description
Chris Hauty is an American screenwriter and novelist best known for his work on action films and political thrillers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Chris Hauty
Target entity description: Chris Hauty is an American screenwriter and novelist best known for his work on action films and political thrillers.
  • A. Michael A. Helfant
    Michael A. Helfant is a film producer and entertainment executive known for his work on genre and thriller projects, including the 2013 crime thriller "The Call."
  • B. Larry Stenger
    Larry Stenger is one of the original founders associated with the early formation of semiconductor company Advanced Micro Devices (AMD).
  • C. Craig A. Stough
    Craig A. Stough is an American local government leader who serves as the mayor of Sylvania, Ohio.
  • D. Michael Goulian
    Michael Goulian is an American aerobatic champion and airshow performer best known for competing at the highest level in international air racing events.
  • E. Mark P. McCahill
    Mark P. McCahill is an American computer scientist best known for pioneering early internet technologies, including creating the Gopher protocol for distributed document search and retrieval.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0067d55ac8190b7a7fce36e6ddf3c completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec89797ac819090fb68bb5f2fad5c completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69fec974f39c819081dcec5c18090cf7 completed May 9, 2026, 5:43 a.m.
NED2 Entity disambiguation (via description) batch_69feca9d1a5c8190b0c649f83a74231b completed May 9, 2026, 5:48 a.m.
Created at: April 10, 2026, 3:10 a.m.