Triple
T15674260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herman Blume |
E377395
|
entity |
| Predicate | hasThemeInStoryline |
P76865
|
FINISHED |
| Object | disillusionment with wealth |
—
|
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: disillusionment with wealth | Statement: [Herman Blume, hasThemeInStoryline, disillusionment with wealth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThemeInStoryline Context triple: [Herman Blume, hasThemeInStoryline, disillusionment with wealth]
-
A.
hasThemeInStory
chosen
Indicates that a particular theme is present or plays a significant role within a given story.
-
B.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
C.
hasSayingTheme
Indicates that a saying, proverb, or quoted expression is about or centers on a particular theme or subject.
-
D.
hasCentralTheme
Indicates that one entity serves as the primary or dominant theme or subject matter of another entity.
-
E.
hasThemeConnection
Indicates a relationship where one entity is linked to another through a shared or related theme, topic, or conceptual focus.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f2c996c8190a9ebe0e92608feaa |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:16 a.m.