Triple
T35095136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lowick |
E1012845
|
entity |
| Predicate | hasThemeInContextOfWork |
P76865
|
FINISHED |
| Object | marital disillusionment |
—
|
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: marital disillusionment | Statement: [Lowick, hasThemeInContextOfWork, marital disillusionment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThemeInContextOfWork Context triple: [Lowick, hasThemeInContextOfWork, marital disillusionment]
-
A.
associatedWithWorkTheme
Indicates a relationship where something is connected or related to a particular work theme or subject matter.
-
B.
hasThemeRelationship
Indicates a relationship where one entity is thematically related to, or centered around, another entity as its main subject or topic.
-
C.
hasRoleInThemes
Indicates that an entity plays a specific role or function within one or more thematic contexts or themes.
-
D.
hasThemeInStory
chosen
Indicates that a particular theme is present or plays a significant role within a given story.
-
E.
hasOccupationTheme
Indicates that something (such as a work or resource) centrally involves or focuses on a particular occupation or type of work as its main theme.
- 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_69f76dd432ec8190969bc32acfc152b1 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7a225a77c81908f8953ccfeb14336 |
completed | May 3, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:01 p.m.