Triple
T9268790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Wiggins |
E222767
|
entity |
| Predicate | moralLessonEmbodied |
P25343
|
FINISHED |
| Object | importance of trees |
—
|
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: importance of trees | Statement: [Ted Wiggins, moralLessonEmbodied, importance of trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralLessonEmbodied Context triple: [Ted Wiggins, moralLessonEmbodied, importance of trees]
-
A.
moralTheme
chosen
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
-
B.
moralRealization
Indicates the recognition or coming to understand a moral truth, principle, or ethical implication about a situation or action.
-
C.
moralExemplarOf
Indicates that one entity serves as a model or standard of moral behavior for another entity or group.
-
D.
moralTrajectory
Indicates the direction and pattern of change in an entity’s moral behavior or ethical stance over time.
-
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_69ca841f2e808190a64f4c31903a1332 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd074ef7408190b213c09491918132 |
completed | April 1, 2026, 11:53 a.m. |
| PD | Predicate disambiguation | batch_69cc7a537bbc8190baee71f556e52a7b |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:33 p.m.