Triple

T28665366
Position Surface form Disambiguated ID Type / Status
Subject How to Survive a Horror Movie E725571 entity
Predicate isFictionalContentAbout P93730 FINISHED
Object fictional horror situations LITERAL 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: fictional horror situations | Statement: [How to Survive a Horror Movie, isFictionalContentAbout, fictional horror situations]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isFictionalContentAbout
Context triple: [How to Survive a Horror Movie, isFictionalContentAbout, fictional horror situations]
  • A. hasFictionalContent chosen
    Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
  • B. isFictionalCharacter
    Indicates that the subject is a character that exists only in fiction rather than in real life.
  • C. hasFictionalType
    Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
  • D. hasFictionalScope
    Indicates that something pertains to, applies within, or is limited to a fictional or imagined context rather than real-world scope.
  • E. worksInFictionalContext
    Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
  • F. None of above.

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_69f01d85be388190b669a0e401e2f2c4 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f6562fd3488190be1acd8c526a28d2 completed May 2, 2026, 7:53 p.m.
PD Predicate disambiguation batch_69f651ac855481908e30c3b345d31356 completed May 2, 2026, 7:34 p.m.
Created at: April 28, 2026, 5 a.m.