Triple
T1200924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Most Dangerous Game (1932 film) |
E25778
|
entity |
| Predicate | setDecorationTheme |
P20708
|
FINISHED |
| Object | gothic hunting lodge |
—
|
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: gothic hunting lodge | Statement: [The Most Dangerous Game (1932 film), setDecorationTheme, gothic hunting lodge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setDecorationTheme Context triple: [The Most Dangerous Game (1932 film), setDecorationTheme, gothic hunting lodge]
-
A.
decorationClass
Indicates that one entity serves as a decorative classification or style category applied to another entity.
-
B.
typeOfDecoration
Indicates the specific kind or style of decoration associated with an entity or applied in a given context.
-
C.
signatureTheme
Indicates that something serves as a distinctive, defining theme strongly associated with a particular entity or context.
-
D.
themedAs
chosen
Indicates that something is characterized, styled, or organized according to a particular theme or motif.
-
E.
decoration
Indicates that one entity serves as an ornament or embellishing element for another entity, enhancing its appearance or style.
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd9ec3488190afe35af54efae5e9 |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.