Triple
T22493953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandner Kaspar |
E556089
|
entity |
| Predicate | moralOrMessage |
P25343
|
FINISHED |
| Object | acceptance of death |
—
|
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: acceptance of death | Statement: [Brandner Kaspar, moralOrMessage, acceptance of death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralOrMessage Context triple: [Brandner Kaspar, moralOrMessage, acceptance of death]
-
A.
hasMoralMessage
Indicates that something conveys or embodies a lesson, value, or guidance about what is right or wrong behavior.
-
B.
moralTheme
chosen
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
-
C.
moralContent
Indicates that something contains, expresses, or conveys moral values, judgments, or ethical significance.
-
D.
moralBelief
Indicates that an agent holds a normative judgment about what is right, wrong, good, or bad in a given context.
-
E.
moralConcept
Indicates that one entity represents or embodies a moral or ethical concept in relation to another.
- 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_69e11e5445bc8190b6a9481926db3355 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15cb0dfb88190a4175e5e95d7ad4b |
completed | April 29, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e898be31448190be5ae7f5656f0497 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:49 p.m.