Triple
T27229944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francisco Bringas |
E682125
|
entity |
| Predicate | moralProfile |
P47751
|
FINISHED |
| Object | austere |
—
|
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: austere | Statement: [Francisco Bringas, moralProfile, austere]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralProfile Context triple: [Francisco Bringas, moralProfile, austere]
-
A.
moralPortrayal
Indicates how an entity is depicted in terms of moral qualities, such as virtue, vice, or ethical standing, within a given context.
-
B.
moralTrajectory
Indicates the direction and pattern of change in an entity’s moral behavior or ethical stance over time.
-
C.
moralAttitude
Indicates a subject’s evaluative stance or judgment about the moral rightness or wrongness of another entity, action, or situation.
-
D.
hasMoralCharacteristic
chosen
Indicates that an entity possesses a particular moral quality, trait, or ethical attribute.
-
E.
moralTendency
Indicates a general inclination or propensity of an entity to act in ways judged as morally right or wrong.
- 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_69eefacdad7881908b7bca61c90a1a1e |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f65876c52c8190bc889c7a67bd07f3 |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 9:46 a.m.