Triple
T17049518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack's mother |
E413655
|
entity |
| Predicate | moralContext |
P53261
|
FINISHED |
| Object | embodies caution and responsibility |
—
|
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: embodies caution and responsibility | Statement: [Jack's mother, moralContext, embodies caution and responsibility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralContext Context triple: [Jack's mother, moralContext, embodies caution and responsibility]
-
A.
moralImplication
Indicates that one situation, action, or state of affairs entails or suggests a particular moral judgment, obligation, or ethical consequence.
-
B.
moralConcept
chosen
Indicates that one entity represents or embodies a moral or ethical concept in relation to another.
-
C.
moralContent
Indicates that something contains, expresses, or conveys moral values, judgments, or ethical significance.
-
D.
moralAttitude
Indicates a subject’s evaluative stance or judgment about the moral rightness or wrongness of another entity, action, or situation.
-
E.
moralCriterion
Indicates that something is being evaluated or classified according to a standard of moral judgment or ethical rightness.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa1aeac81909e8d97bd708c6b71 |
completed | April 18, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.