Triple

T1677998
Position Surface form Disambiguated ID Type / Status
Subject Four Weddings and a Funeral E36275 entity
Predicate mainCharacter P1183 FINISHED
Object Carrie
Carrie is the charming and enigmatic American woman who becomes the central love interest in the British romantic comedy film "Four Weddings and a Funeral."
 E190392 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: Carrie | Statement: [Four Weddings and a Funeral, mainCharacter, Carrie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Carrie
Context triple: [Four Weddings and a Funeral, mainCharacter, Carrie]
  • A. Carrie
    "Carrie" is Stephen King's debut horror novel, centered on a bullied teenage girl with telekinetic powers who exacts a devastating revenge on her tormentors.
  • B. Misery
    Misery is a psychological horror novel by Stephen King about a famous author held captive by his deranged “number one fan.”
  • C. Misery
    Misery is the first major section of the Heidelberg Catechism, focusing on humanity’s sinfulness and need for redemption.
  • D. Salem's Lot
    Salem's Lot is a horror novel by Stephen King about a small town slowly overtaken by vampires.
  • E. The Fog
    The Fog is a 1980 supernatural horror film directed by John Carpenter, centered on a coastal town haunted by vengeful ghosts who return shrouded in an eerie, glowing mist.
  • 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: Carrie
Triple: [Four Weddings and a Funeral, mainCharacter, Carrie]
Generated description
Carrie is the charming and enigmatic American woman who becomes the central love interest in the British romantic comedy film "Four Weddings and a Funeral."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Carrie
Target entity description: Carrie is the charming and enigmatic American woman who becomes the central love interest in the British romantic comedy film "Four Weddings and a Funeral."
  • A. Carrie
    "Carrie" is Stephen King's debut horror novel, centered on a bullied teenage girl with telekinetic powers who exacts a devastating revenge on her tormentors.
  • B. Misery
    Misery is the first major section of the Heidelberg Catechism, focusing on humanity’s sinfulness and need for redemption.
  • C. Misery
    Misery is a psychological horror novel by Stephen King about a famous author held captive by his deranged “number one fan.”
  • D. Salem's Lot
    Salem's Lot is a horror novel by Stephen King about a small town slowly overtaken by vampires.
  • E. The Fog
    The Fog is a 1980 supernatural horror film directed by John Carpenter, centered on a coastal town haunted by vengeful ghosts who return shrouded in an eerie, glowing mist.
  • 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_69a886139ed081909af0940aa9313512 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa625f7e1081909c3c4fe76625783a completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad71ba4db08190a532fb334fd0cd23 completed March 8, 2026, 12:55 p.m.
NEDg Description generation batch_69ad73cfce488190b0ed6b85713281d3 completed March 8, 2026, 1:04 p.m.
NED2 Entity disambiguation (via description) batch_69ad74401cbc8190bfaba1e9f32810bc completed March 8, 2026, 1:06 p.m.
Created at: March 4, 2026, 7:29 p.m.