Triple
T1350930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arline Greenbaum |
E28878
|
entity |
| Predicate | hasThemeInAssociatedWorks |
P24746
|
FINISHED |
| Object | love during terminal illness |
—
|
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: love during terminal illness | Statement: [Arline Greenbaum, hasThemeInAssociatedWorks, love during terminal illness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThemeInAssociatedWorks Context triple: [Arline Greenbaum, hasThemeInAssociatedWorks, love during terminal illness]
-
A.
hasPersonalThemes
chosen
Indicates that something (such as a work, message, or expression) involves themes that are personal, intimate, or directly related to an individual’s own experiences or inner life.
-
B.
followsInTheme
Indicates that one element continues or succeeds another while maintaining the same theme or thematic context.
-
C.
hasThemeConnection
Indicates a relationship where one entity is linked to another through a shared or related theme, topic, or conceptual focus.
-
D.
hasCentralTheme
Indicates that one entity serves as the primary or dominant theme or subject matter of another entity.
-
E.
containsThemeArea
Indicates that one entity includes or encompasses a specific thematic area as part of its scope or content.
- 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_69a498571d248190a0ac9eb02d97097f |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c26981d081909ca3b8d8cdf7cf2e |
completed | March 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69a4bef5857c81909ae984feb85a26ca |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.