Triple
T5248243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pradosha vrata |
E118515
|
entity |
| Predicate | specialForm |
P7025
|
FINISHED |
| Object | Maha Pradosha vrata |
—
|
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: Maha Pradosha vrata | Statement: [Pradosha vrata, specialForm, Maha Pradosha vrata]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specialForm Context triple: [Pradosha vrata, specialForm, Maha Pradosha vrata]
-
A.
specialCaseOf
chosen
Indicates that one entity represents a more specific, exceptional, or restricted instance of the general situation, rule, or relationship expressed by another entity.
-
B.
specialValue
Indicates that an entity possesses a distinguished or exceptional value compared to typical or default values in the given context.
-
C.
logicalForm
Indicates a relationship where an expression is associated with its structured, formal logical representation.
-
D.
specialComposition
Indicates that one entity is composed of another in a distinctive or non-standard way, highlighting a particular or exceptional form of composition between them.
-
E.
standardFormulation
Indicates that something is expressed or represented in a conventional, officially accepted, or commonly used form or version.
- 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_69bd4468aacc8190a8196f71855cdf4f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b77165c8190bd1ce8a197cef226 |
completed | March 20, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69bd77c30bac8190a883ca45da35d667 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:50 p.m.