Triple
T27362418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Closet Monster |
E685861
|
entity |
| Predicate | hasBodyHorrorElements |
P178019
|
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: [Closet Monster, hasBodyHorrorElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodyHorrorElements Context triple: [Closet Monster, hasBodyHorrorElements, true]
-
A.
hasHorrorElements
Indicates that something contains features, themes, or stylistic aspects characteristic of the horror genre.
-
B.
hasHorrorSubgenre
Indicates that a horror work is classified as belonging to a specific horror subgenre.
-
C.
usesHorrorAsMetaphorFor
Indicates that something employs horror elements or themes as a symbolic device to represent, comment on, or explore another concept, issue, or experience.
-
D.
hasSupernaturalOrSciFiElement
Indicates that the related entity involves, features, or is characterized by supernatural, fantastical, or science-fiction elements beyond ordinary reality.
-
E.
containsSupernaturalElement
Indicates that the subject involves or features a supernatural, magical, or otherworldly element beyond normal natural laws.
- F. None of above. chosen
Provenance (4 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_69ef14887c288190931b8431fdbf53c4 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69f707f380388190954b79d52a321921 |
completed | May 3, 2026, 8:31 a.m. |
Created at: April 27, 2026, 11:54 a.m.