Triple
T3745471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Earth |
E81198
|
entity |
| Predicate | moralState |
P47751
|
FINISHED |
| Object | perfect righteousness |
—
|
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: perfect righteousness | Statement: [New Earth, moralState, perfect righteousness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralState Context triple: [New Earth, moralState, perfect righteousness]
-
A.
moralStatus
Indicates the ethical standing or degree of moral consideration that one entity has in relation to another.
-
B.
hasMoralCharacteristic
chosen
Indicates that an entity possesses a particular moral quality, trait, or ethical attribute.
-
C.
moralExpectation
Indicates that one entity is expected, by moral or ethical standards, to behave in a certain way toward another entity or in a given situation.
-
D.
moralTheme
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
-
E.
moralTone
Indicates the evaluative moral quality or ethical character expressed in or associated with an action, statement, or situation.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb680ddc819094205beb342699f9 |
completed | March 8, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69adc04adebc819088d7f36d0ac343a6 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.