Triple
T17294047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aaron Greidinger |
E419858
|
entity |
| Predicate | hasThemeInLife |
P62774
|
FINISHED |
| Object | moral ambiguity |
—
|
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: moral ambiguity | Statement: [Aaron Greidinger, hasThemeInLife, moral ambiguity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThemeInLife Context triple: [Aaron Greidinger, hasThemeInLife, moral ambiguity]
-
A.
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.
-
B.
hasThemeInStory
Indicates that a particular theme is present or plays a significant role within a given story.
-
C.
hasSayingTheme
Indicates that a saying, proverb, or quoted expression is about or centers on a particular theme or subject.
-
D.
hasThemeType
chosen
Indicates that something is associated with or characterized by a particular thematic category or type.
-
E.
hasFamilyTheme
Indicates that something involves, centers on, or prominently features themes related to family relationships or family life.
- 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e437869ec08190b4a63fb1ee6a71ee |
completed | April 19, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69e3b0118ad08190b119cd219c68ba67 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:40 a.m.