Triple
T14486722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Ma |
E359246
|
entity |
| Predicate | virtuePraisedInSources |
P89611
|
FINISHED |
| Object | frugality |
—
|
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: frugality | Statement: [Empress Ma, virtuePraisedInSources, frugality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: virtuePraisedInSources Context triple: [Empress Ma, virtuePraisedInSources, frugality]
-
A.
virtuePraisedFor
chosen
Indicates that a particular virtue is being commended, admired, or spoken of approvingly by someone.
-
B.
virtuePromoted
Indicates that one entity actively encourages, supports, or increases the presence or practice of a particular virtue in another entity or context.
-
C.
vowedVirtue
Indicates that an entity has formally promised or committed to uphold a particular virtue or moral quality.
-
D.
virtueIllustrated
Indicates that an action, example, or situation serves to demonstrate or make clear a particular virtue.
-
E.
virtue
Indicates that an entity possesses or exemplifies a morally good quality, trait, or behavior.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924ee0f08190baf68318b41fa64d |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.