Triple
T18297096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malcolm Lowry |
E438257
|
entity |
| Predicate | hasThemeInWorks |
P81453
|
FINISHED |
| Object | alcoholism |
—
|
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: alcoholism | Statement: [Malcolm Lowry, hasThemeInWorks, alcoholism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThemeInWorks Context triple: [Malcolm Lowry, hasThemeInWorks, alcoholism]
-
A.
hasThemeInStory
Indicates that a particular theme is present or plays a significant role within a given story.
-
B.
hasPersonalThemes
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.
-
C.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
D.
hasWorksAbout
chosen
Indicates that one entity (such as a creator, collection, or source) includes or is associated with works whose subject or focus is 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5017c0f04819095cd9d59afc37caa |
completed | April 19, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.