Triple
T2885708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ghost in the Mill |
E59499
|
entity |
| Predicate | hasMoralPurpose |
P42577
|
FINISHED |
| Object | didactic |
—
|
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: didactic | Statement: [The Ghost in the Mill, hasMoralPurpose, didactic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoralPurpose Context triple: [The Ghost in the Mill, hasMoralPurpose, didactic]
-
A.
hasMoralPerspective
Indicates that an entity holds or applies a particular moral or ethical viewpoint in evaluating actions, situations, or other entities.
-
B.
hasMoralArc
Indicates that something follows a discernible trajectory of moral development, progress, or decline over time.
-
C.
derivesMoralityFrom
Indicates that one entity bases or grounds its moral principles, judgments, or ethical framework on another entity.
-
D.
hasTheologicalPurpose
Indicates that something is intended or designed to serve a religious or theological function or goal.
-
E.
hasEthicalDimension
Indicates that the relationship, action, or situation involves moral considerations, value judgments, or ethical implications.
- F. None of above. chosen
Provenance (4 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_69ab4ac739188190a112f42a5a69c951 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abe04476588190b0db0880e14c79b5 |
completed | March 7, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69abdd15cbf08190bf7fea5ea516848a |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdd96670c8190b727f9ac27dadf67 |
completed | March 7, 2026, 8:11 a.m. |
Created at: March 6, 2026, 10:03 p.m.