Triple
T6109533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuestra Señora de la Merced |
E136198
|
entity |
| Predicate | linkedVirtue |
P6827
|
FINISHED |
| Object | charity |
—
|
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: charity | Statement: [Nuestra Señora de la Merced, linkedVirtue, charity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedVirtue Context triple: [Nuestra Señora de la Merced, linkedVirtue, charity]
-
A.
virtue
chosen
Indicates that an entity possesses or exemplifies a morally good quality, trait, or behavior.
-
B.
vowedVirtue
Indicates that an entity has formally promised or committed to uphold a particular virtue or moral quality.
-
C.
virtueIllustrated
Indicates that an action, example, or situation serves to demonstrate or make clear a particular virtue.
-
D.
viewsAsVirtue
Indicates that one entity regards a particular trait, behavior, or quality as a moral virtue.
-
E.
moralAssociation
Indicates a perceived ethical or moral connection between entities, such as one influencing or reflecting the moral character, values, or judgment of the other.
- 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_69c0089ea6f88190b349be53e04b4f5f |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b84ed088190a12cdb844d743326 |
completed | March 22, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c049f80e2081909b7d84a104cda68d |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:13 p.m.