Triple
T19594699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mata Kausalya |
E470320
|
entity |
| Predicate | ethicalSymbolism |
P53261
|
FINISHED |
| Object | ideal motherhood |
—
|
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: ideal motherhood | Statement: [Mata Kausalya, ethicalSymbolism, ideal motherhood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethicalSymbolism Context triple: [Mata Kausalya, ethicalSymbolism, ideal motherhood]
-
A.
ethicalDebate
Indicates a relationship where parties are engaged in discussing, questioning, or disputing the moral rightness or wrongness of actions, policies, or principles.
-
B.
ethicalQuality
Indicates that an entity possesses a moral or ethical characteristic, such as goodness, virtue, or integrity, as evaluated by some ethical standard.
-
C.
moralImplication
Indicates that one situation, action, or state of affairs entails or suggests a particular moral judgment, obligation, or ethical consequence.
-
D.
moralConcept
chosen
Indicates that one entity represents or embodies a moral or ethical concept in relation to another.
-
E.
moralTheme
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640793cd88190b9b84491bfb2493f |
completed | April 20, 2026, 3:04 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:43 p.m.