Triple
T4620199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | March (graphic novel trilogy) |
E100958
|
entity |
| Predicate | frameStoryEvent |
P36137
|
FINISHED |
| Object | Barack Obama’s 2009 presidential inauguration |
—
|
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: Barack Obama’s 2009 presidential inauguration | Statement: [March (graphic novel trilogy), frameStoryEvent, Barack Obama’s 2009 presidential inauguration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frameStoryEvent Context triple: [March (graphic novel trilogy), frameStoryEvent, Barack Obama’s 2009 presidential inauguration]
-
A.
narrativeFrame
Indicates the overarching narrative context or perspective within which events, actions, or relationships are presented or interpreted.
-
B.
storyElement
Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
-
C.
storyFunction
Indicates that one entity serves a particular narrative role or function within the story structure of another entity.
-
D.
storyBy
Indicates that one entity is the creator or author of the story associated with another entity.
-
E.
narrativeEpisode
chosen
Indicates that one event, scene, or segment functions as a distinct episode within a larger narrative or storyline.
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59e560f481908abb1a97b4ff5795 |
completed | March 20, 2026, 2:29 p.m. |
| PD | Predicate disambiguation | batch_69bd5231db7c8190b38d4fdbad8bf842 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:12 p.m.