Triple
T19594464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen of Ayodhya |
E470314
|
entity |
| Predicate | laterEmotion |
P68366
|
FINISHED |
| Object | repentance for causing Rama’s exile |
—
|
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: repentance for causing Rama’s exile | Statement: [Queen of Ayodhya, laterEmotion, repentance for causing Rama’s exile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterEmotion Context triple: [Queen of Ayodhya, laterEmotion, repentance for causing Rama’s exile]
-
A.
secondaryEmotion
chosen
Indicates that one emotion arises as a secondary, derivative, or reactive feeling in response to a primary emotion.
-
B.
intendedEmotion
Indicates the emotion that an action, expression, or communication is meant to evoke in its target, regardless of the actual emotion experienced.
-
C.
emotionState
Indicates the emotional condition or feeling that an entity is currently experiencing.
-
D.
emotionDisplayed
Indicates that an entity is outwardly expressing or showing a particular emotion.
-
E.
emotionEffect
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
- 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.