Triple
T16225995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dark Knight |
E393844
|
entity |
| Predicate | hasThemedScenery |
P71590
|
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: [Dark Knight, hasThemedScenery, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThemedScenery Context triple: [Dark Knight, hasThemedScenery, true]
-
A.
hasThemedLand
Indicates that one entity (typically a larger venue or park) includes or is composed of a specific themed land or area as part of its layout or structure.
-
B.
hasThematicPavilion
Indicates that an entity includes or is associated with a specific thematic pavilion as part of its structure or offerings.
-
C.
hasFloodTheme
Indicates that something incorporates, depicts, or centers around the theme of a flood or flooding.
-
D.
hasScenicResource
chosen
Indicates that an entity possesses or is associated with a natural or visual feature valued for its aesthetic or scenic qualities.
-
E.
hasFestivalTheme
Indicates that something is associated with, characterized by, or designed around a particular festival-related theme.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d25f8bc81909aa59b794a528db2 |
completed | April 17, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.