Triple

T2351250
Position Surface form Disambiguated ID Type / Status
Subject Midsommar E47452 entity
Predicate mainCharacter P1183 FINISHED
Object Connie
Connie is a supporting character in the 2019 folk horror film "Midsommar," one of the visiting outsiders who becomes entangled in the sinister rituals of a remote Swedish commune.
 E257893 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: Connie | Statement: [Midsommar, mainCharacter, Connie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Connie
Context triple: [Midsommar, mainCharacter, Connie]
  • A. Carla
    Carla is a feminine given name commonly used in various languages, often considered the female form of Carl or Charles.
  • B. Lori
    Lori is a feminine given name commonly used in English-speaking countries, often as a diminutive of Laura or Lorraine.
  • C. Cynthia
    Cynthia is a common feminine given name used in various cultures, often associated with the Greek moon goddess Artemis.
  • D. Molly Stark
    Molly Stark was the wife of American Revolutionary War General John Stark, remembered in part through his famous battle cry invoking her name at the Battle of Bennington.
  • E. Suzanne
    "Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
  • 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: Connie
Triple: [Midsommar, mainCharacter, Connie]
Generated description
Connie is a supporting character in the 2019 folk horror film "Midsommar," one of the visiting outsiders who becomes entangled in the sinister rituals of a remote Swedish commune.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Connie
Target entity description: Connie is a supporting character in the 2019 folk horror film "Midsommar," one of the visiting outsiders who becomes entangled in the sinister rituals of a remote Swedish commune.
  • A. Carla
    Carla is a feminine given name commonly used in various languages, often considered the female form of Carl or Charles.
  • B. Lori
    Lori is a feminine given name commonly used in English-speaking countries, often as a diminutive of Laura or Lorraine.
  • C. Cynthia
    Cynthia is a common feminine given name used in various cultures, often associated with the Greek moon goddess Artemis.
  • D. Molly Stark
    Molly Stark was the wife of American Revolutionary War General John Stark, remembered in part through his famous battle cry invoking her name at the Battle of Bennington.
  • E. Suzanne
    "Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
  • 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_69a88a1b678c8190bce986922ba60ce0 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc6f75d888190a2e41edaa532e83f completed March 7, 2026, 6:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae962f769881909a7713880eaa9b84 completed March 9, 2026, 9:43 a.m.
NEDg Description generation batch_69ae96b399608190bfa846c433612142 completed March 9, 2026, 9:45 a.m.
NED2 Entity disambiguation (via description) batch_69ae977e539c81909cef638cc61e5ec1 completed March 9, 2026, 9:48 a.m.
Created at: March 4, 2026, 7:54 p.m.