Triple

T10121296
Position Surface form Disambiguated ID Type / Status
Subject Sue Snell E223295 entity
Predicate appearsIn P795 FINISHED
Object Carrie E22626 NE FINISHED

How this triple was built (2 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: [Sue Snell, appearsIn, Carrie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carrie
Context triple: [Sue Snell, appearsIn, Carrie]
  • A. Carrie chosen
    "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. 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."
  • C. Carrie
    Carrie is a feminine given name commonly used in English-speaking countries, often as a diminutive of Caroline or Carol.
  • D. Misery
    Misery is the first major section of the Heidelberg Catechism, focusing on humanity’s sinfulness and need for redemption.
  • E. Misery
    Misery is a psychological horror novel by Stephen King about a famous author held captive by his deranged “number one fan.”
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8422047c81909d66b717b8b18cf3 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd266b18c8190b35fe637c912e756 completed April 2, 2026, 2:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cc493db88190b3b09a77b82b3cc9 completed April 5, 2026, 8:55 p.m.
Created at: March 30, 2026, 9:04 p.m.