Triple
T19594833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rishyamukha |
E470324
|
entity |
| Predicate | reasonForSafety |
P56024
|
FINISHED |
| Object | Vali was under a curse not to approach Rishyamukha |
—
|
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: Vali was under a curse not to approach Rishyamukha | Statement: [Rishyamukha, reasonForSafety, Vali was under a curse not to approach Rishyamukha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForSafety Context triple: [Rishyamukha, reasonForSafety, Vali was under a curse not to approach Rishyamukha]
-
A.
safetyRationale
chosen
Indicates the reasoning or justification provided to explain how and why something is considered safe or made safe.
-
B.
reasonForUse
Indicates that one entity specifies the justification, purpose, or motivation for using another entity.
-
C.
reasonForSpecialMeasures
Indicates that one entity specifies the justification or cause for which special measures or exceptional actions are taken regarding another entity.
-
D.
safetyBenefit
Indicates that one entity provides, contributes to, or results in an improvement in the safety or risk reduction experienced by another entity.
-
E.
reasonForSuppression
Indicates the justification or cause for which something (such as information, data, or content) has been withheld, hidden, or prevented from being shown or used.
- 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.