Triple

T9345311
Position Surface form Disambiguated ID Type / Status
Subject Lisa Sheridan E224873 entity
Predicate protagonistOf P9202 FINISHED
Object Obsessed
Obsessed is a psychological thriller film centered on a woman whose dangerous fixation threatens the life and marriage of the character played by Lisa Sheridan.
 E792976 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: Obsessed | Statement: [Lisa Sheridan, protagonistOf, Obsessed]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Obsessed
Context triple: [Lisa Sheridan, protagonistOf, Obsessed]
  • A. Obsessed
    Obsessed is a work by creator Ken Seng, recognized as one of his notable contributions to his field.
  • B. Obsessed
    "Obsessed" is a 2009 R&B/pop single by Mariah Carey, known for its confrontational lyrics and catchy hook, widely interpreted as a response to rapper Eminem.
  • C. Obsessed
    "Obsessed" is a country-pop studio album by American duo Dan + Shay, featuring romantic, harmony-rich tracks that helped solidify their mainstream success.
  • D. Obsessed
    Obsessed is a social media account or online persona that is followed by the user Cinco.
  • E. Obsessed
    Obsessed is a 2009 psychological thriller film starring Idris Elba, Beyoncé, and Ali Larter about a successful executive whose life unravels when a temp employee becomes dangerously fixated on him.
  • 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: Obsessed
Triple: [Lisa Sheridan, protagonistOf, Obsessed]
Generated description
Obsessed is a psychological thriller film centered on a woman whose dangerous fixation threatens the life and marriage of the character played by Lisa Sheridan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Obsessed
Target entity description: Obsessed is a psychological thriller film centered on a woman whose dangerous fixation threatens the life and marriage of the character played by Lisa Sheridan.
  • A. Obsessed
    Obsessed is a 2009 psychological thriller film starring Idris Elba, Beyoncé, and Ali Larter about a successful executive whose life unravels when a temp employee becomes dangerously fixated on him.
  • B. Obsessed
    "Obsessed" is a crime thriller novel in the Michael Bennett series by James Patterson, following the NYPD detective as he tackles a particularly personal and dangerous case.
  • C. Obsessed
    Obsessed is a social media account or online persona that is followed by the user Cinco.
  • D. Obsessed
    "Obsessed" is a 2009 R&B/pop single by Mariah Carey, known for its confrontational lyrics and catchy hook, widely interpreted as a response to rapper Eminem.
  • E. Obsessed
    Obsessed is a work by creator Ken Seng, recognized as one of his notable contributions to his field.
  • 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_69ca842993248190a79ab06968994b86 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4f0ce7b881908714ab526d94fa1d completed April 1, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e41ccdcc8190b2939716984b2c7b completed April 4, 2026, 10:12 a.m.
NEDg Description generation batch_69d0e5752a38819089b23ac52f0a6a39 completed April 4, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_69d0e64cb4dc81908cef7d729d9cfb4d completed April 4, 2026, 10:22 a.m.
Created at: March 30, 2026, 7:41 p.m.