Triple

T11394335
Position Surface form Disambiguated ID Type / Status
Subject Lady in the Dark (1944 film) E269927 entity
Predicate starring P1507 FINISHED
Object Jon Hall
Jon Hall was an American film actor best known for his leading-man roles in 1940s adventure and fantasy movies.
E926964 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: Jon Hall | Statement: [Lady in the Dark (1944 film), starring, Jon Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jon Hall
Context triple: [Lady in the Dark (1944 film), starring, Jon Hall]
  • A. Ian Hill
    Ian Hill is an English bassist best known as a founding member of the heavy metal band Judas Priest.
  • B. Jerry Horton
    Jerry Horton is an American guitarist best known as the lead guitarist and a founding member of the rock band Papa Roach.
  • C. Grant Wistrom
    Grant Wistrom is a former American football defensive end best known for his standout college career at the University of Nebraska and his Super Bowl–winning tenure in the NFL with the St. Louis Rams.
  • D. Ian Hallard
    Ian Hallard is a British actor and writer known for his work in television, theatre, and radio, as well as for his collaborations with his husband, writer-actor Mark Gatiss.
  • E. Glen Tullman
    Glen Tullman is an American healthcare technology entrepreneur and executive best known for leading and building major digital health companies, including Allscripts.
  • 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: Jon Hall
Triple: [Lady in the Dark (1944 film), starring, Jon Hall]
Generated description
Jon Hall was an American film actor best known for his leading-man roles in 1940s adventure and fantasy movies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jon Hall
Target entity description: Jon Hall was an American film actor best known for his leading-man roles in 1940s adventure and fantasy movies.
  • A. Ian Hill
    Ian Hill is an English bassist best known as a founding member of the heavy metal band Judas Priest.
  • B. Jerry Horton
    Jerry Horton is an American guitarist best known as the lead guitarist and a founding member of the rock band Papa Roach.
  • C. Grant Wistrom
    Grant Wistrom is a former American football defensive end best known for his standout college career at the University of Nebraska and his Super Bowl–winning tenure in the NFL with the St. Louis Rams.
  • D. Ian Hallard
    Ian Hallard is a British actor and writer known for his work in television, theatre, and radio, as well as for his collaborations with his husband, writer-actor Mark Gatiss.
  • E. Glen Tullman
    Glen Tullman is an American healthcare technology entrepreneur and executive best known for leading and building major digital health companies, including Allscripts.
  • 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_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d80018a58c81908b80dc9abd18d650 completed April 9, 2026, 7:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5e8cc338081908da977b5b7c6bef3 completed April 20, 2026, 8:50 a.m.
NEDg Description generation batch_69e5f1557e9c8190b53ce391793b2c7f completed April 20, 2026, 9:26 a.m.
NED2 Entity disambiguation (via description) batch_69e5f863bf7c81908969ed0a5b99f032 completed April 20, 2026, 9:56 a.m.
Created at: April 8, 2026, 9:34 p.m.