Triple
T12799898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Train Boy |
E305986
|
entity |
| Predicate | intendedMoralLesson |
P25343
|
FINISHED |
| Object | success comes from hard work and integrity |
—
|
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: success comes from hard work and integrity | Statement: [The Train Boy, intendedMoralLesson, success comes from hard work and integrity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedMoralLesson Context triple: [The Train Boy, intendedMoralLesson, success comes from hard work and integrity]
-
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.
moralOfMyth
Indicates the underlying lesson, ethical teaching, or message conveyed by a myth.
-
D.
moralImplication
Indicates that one situation, action, or state of affairs entails or suggests a particular moral judgment, obligation, or ethical consequence.
-
E.
derivesMoralityFrom
Indicates that one entity bases or grounds its moral principles, judgments, or ethical framework on another entity.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e6f858c8190915ede38e9a6a2df |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d9640ed7448190b276e7fab649f7d2 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:30 p.m.