Triple
T15710685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Berg |
E380828
|
entity |
| Predicate | majorThemeInStory |
P49998
|
FINISHED |
| Object | guilt |
—
|
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: guilt | Statement: [Michael Berg, majorThemeInStory, guilt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorThemeInStory Context triple: [Michael Berg, majorThemeInStory, guilt]
-
A.
majorThemeAssociation
chosen
Indicates that one entity is associated with another as a primary or central theme.
-
B.
narrativeMotif
Indicates a recurring thematic element, pattern, or situation that appears across one or more narratives and helps structure or convey their underlying meanings.
-
C.
characterTheme
Indicates that a particular theme, motif, or conceptual focus is associated with a given character.
-
D.
mainThemeCharacter
Indicates that a character serves as the central or primary figure associated with the main theme of a work or narrative.
-
E.
fictionalTheme
Indicates that a work, element, or context is centered around or characterized by a fictional theme or motif.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f8f5d6081908243fa59b46b7c76 |
completed | April 16, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:45 a.m.