Triple
T26385168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harper Stewart |
E663256
|
entity |
| Predicate | moralFlaw |
P102732
|
FINISHED |
| Object | tendency to prioritize career over honesty |
—
|
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: tendency to prioritize career over honesty | Statement: [Harper Stewart, moralFlaw, tendency to prioritize career over honesty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralFlaw Context triple: [Harper Stewart, moralFlaw, tendency to prioritize career over honesty]
-
A.
moralFailing
chosen
Indicates that an entity exhibits a flaw or shortcoming in moral character or ethical behavior.
-
B.
isMoralFoilFor
Indicates that one entity serves as a contrasting counterpart whose differing moral qualities highlight or emphasize the moral traits of another entity.
-
C.
hasMoralCharacteristic
Indicates that an entity possesses a particular moral quality, trait, or ethical attribute.
-
D.
moralTendency
Indicates a general inclination or propensity of an entity to act in ways judged as morally right or wrong.
-
E.
explainsMoralFailureAs
Indicates that one party interprets or accounts for another party’s moral failing in terms of a particular cause, reason, or framework.
- 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_69ee88374adc81909868f3bab374a32f |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f610784f7481908cc17baeac8a23e4 |
completed | May 2, 2026, 2:55 p.m. |
| PD | Predicate disambiguation | batch_69f602d2ec748190ae95154f34c7878f |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 11:21 p.m.