Triple
T10394567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evil (TV series episodes) |
E244977
|
entity |
| Predicate | storyEngine |
P93683
|
FINISHED |
| Object | evaluation of miracles and demonic activity |
—
|
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: evaluation of miracles and demonic activity | Statement: [Evil (TV series episodes), storyEngine, evaluation of miracles and demonic activity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyEngine Context triple: [Evil (TV series episodes), storyEngine, evaluation of miracles and demonic activity]
-
A.
storyFunction
Indicates that one entity serves a particular narrative role or function within the story structure of another entity.
-
B.
storyElement
Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
-
C.
storyBy
Indicates that one entity is the creator or author of the story associated with another entity.
-
D.
storyWorld
Indicates the fictional universe or narrative setting within which a story, event, or character exists or takes place.
-
E.
storyTitle
Indicates that one entity is the title assigned to a story associated with another entity.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9b795fc8190aa50ce3c7360ff83 |
completed | April 7, 2026, 11:25 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb438c481908dff87c47de2f069 |
completed | April 7, 2026, 10:43 a.m. |
| PDg | Predicate description generation | batch_69d4e944fac4819093b0312aa0efd729 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, 12:06 p.m.