Triple
T35355606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joan Johnson |
E1021313
|
entity |
| Predicate | centralThemeOfStoryInvolvingCharacter |
P39449
|
FINISHED |
| Object | family abuse |
—
|
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: family abuse | Statement: [Joan Johnson, centralThemeOfStoryInvolvingCharacter, family abuse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: centralThemeOfStoryInvolvingCharacter Context triple: [Joan Johnson, centralThemeOfStoryInvolvingCharacter, family abuse]
-
A.
characterTheme
chosen
Indicates that a particular theme, motif, or conceptual focus is associated with a given character.
-
B.
thematicCharacter
Indicates that an entity serves as a central or recurring figure embodying key themes or motifs within a narrative or discourse.
-
C.
mainThemeCharacter
Indicates that a character serves as the central or primary figure associated with the main theme of a work or narrative.
-
D.
mainSettingOfStory
Indicates that a location or environment serves as the primary setting in which the events of a story take place.
-
E.
primaryStoryThemes
Indicates the main recurring ideas or motifs that characterize and unify a story’s narrative.
- 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_69f76def44c881908a20e8008572eb44 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fda5003cdc8190a558501271389912 |
completed | May 8, 2026, 8:55 a.m. |
| PD | Predicate disambiguation | batch_69fda05bfc2c819096821a5300e9bb24 |
completed | May 8, 2026, 8:35 a.m. |
Created at: May 3, 2026, 4:03 p.m.