Triple

T4626327
Position Surface form Disambiguated ID Type / Status
Subject The Other Man E101105 entity
Predicate mainCharacter P1183 FINISHED
Object Lisa
Lisa is the central female protagonist of the film "The Other Man," around whom the story’s romantic and dramatic tensions revolve.
 E457471 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: Lisa | Statement: [The Other Man, mainCharacter, Lisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lisa
Context triple: [The Other Man, mainCharacter, Lisa]
  • A. Lisa
    Lisa is a central character in the science fiction adventure film "Zathura: A Space Adventure," where she becomes unwittingly involved in her younger brothers' perilous journey through outer space.
  • B. Lisa
    Lisa is the given name of Australian musician and composer Lisa Gerrard, renowned for her work as part of Dead Can Dance and for her film scores.
  • C. Lisa
    Lisa is the central protagonist of the film "Wicker Park," around whom the story’s romantic mystery and emotional tension revolve.
  • D. Lisa
    Lisa is a feminine given name commonly used in English-speaking countries, often as a shortened form of Elizabeth or Melissa.
  • E. Laura
    Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
  • 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: Lisa
Triple: [The Other Man, mainCharacter, Lisa]
Generated description
Lisa is the central female protagonist of the film "The Other Man," around whom the story’s romantic and dramatic tensions revolve.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lisa
Target entity description: Lisa is the central female protagonist of the film "The Other Man," around whom the story’s romantic and dramatic tensions revolve.
  • A. Lisa
    Lisa is a central character in the science fiction adventure film "Zathura: A Space Adventure," where she becomes unwittingly involved in her younger brothers' perilous journey through outer space.
  • B. Lisa
    Lisa is the given name of Australian musician and composer Lisa Gerrard, renowned for her work as part of Dead Can Dance and for her film scores.
  • C. Lisa
    Lisa is the central protagonist of the film "Wicker Park," around whom the story’s romantic mystery and emotional tension revolve.
  • D. Lisa
    Lisa is a feminine given name commonly used in English-speaking countries, often as a shortened form of Elizabeth or Melissa.
  • E. Laura
    Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a0a7b588190bc6552ee5babb198 completed March 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaab30508190881828adab92ba22 completed March 21, 2026, 1:55 a.m.
NEDg Description generation batch_69bdfb56021081909b23d22770bf3c88 completed March 21, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_69bdfbf15f1481908b76bcdd37ebd4ce completed March 21, 2026, 2:01 a.m.
Created at: March 20, 2026, 1:13 p.m.