Triple
T36135262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Dreams |
E1045147
|
entity |
| Predicate | hasDarkFantasyElements |
P155287
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Bad Dreams, hasDarkFantasyElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDarkFantasyElements Context triple: [Bad Dreams, hasDarkFantasyElements, true]
-
A.
hasHorrorElements
Indicates that something contains features, themes, or stylistic aspects characteristic of the horror genre.
-
B.
hasSupernaturalOrSciFiElement
chosen
Indicates that the related entity involves, features, or is characterized by supernatural, fantastical, or science-fiction elements beyond ordinary reality.
-
C.
hasDarkAesthetic
Indicates that something embodies or is characterized by a visually dark, moody, or gothic style or atmosphere.
-
D.
typeOfDarkness
Indicates a relationship where one entity is characterized as a specific kind or form of darkness relative to another.
-
E.
containsSupernaturalElement
Indicates that the subject involves or features a supernatural, magical, or otherworldly element beyond normal natural laws.
- 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_69f76e36a4508190b5bfc8f594272a4c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b69b333081909cadbed3fcb8ecf5 |
completed | May 3, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c2a5f8819094ad4621d7b97e0c |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:08 p.m.