Triple
T31616836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordan Lyman |
E806779
|
entity |
| Predicate | storyResolutionRole |
P161981
|
FINISHED |
| Object | exposes coup plot |
—
|
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: exposes coup plot | Statement: [Jordan Lyman, storyResolutionRole, exposes coup plot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyResolutionRole Context triple: [Jordan Lyman, storyResolutionRole, exposes coup plot]
-
A.
resolvedByCharacter
chosen
Indicates that a particular issue, conflict, or problem is brought to a conclusion or solved through the actions or decisions of a specific character.
-
B.
resolutionInStory
Indicates the part of a narrative where the central conflicts are resolved and the story’s outcomes are finalized.
-
C.
roleInStories
Indicates the specific function, position, or character part an entity plays within one or more stories.
-
D.
roleForProtagonist
Indicates the specific narrative or functional role that an entity plays in relation to the story’s main protagonist.
-
E.
inNarrativeRole
Indicates that one entity participates in relation to another by occupying a specific narrative function or role within a story or discourse.
- 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_69f348d61f2081908cad94bc9ffbb671 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 30, 2026, 10:39 p.m.