Triple
T6194807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Praśna Upanishad |
E138482
|
entity |
| Predicate | hasQuestionCount |
P15109
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Praśna Upanishad, hasQuestionCount, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQuestionCount Context triple: [Praśna Upanishad, hasQuestionCount, 6]
-
A.
numberOfQuestions
chosen
Indicates the total count of questions associated with or contained in a given entity or context.
-
B.
hasOpenQuestions
Indicates that there are unresolved or unanswered issues, problems, or inquiries associated with the referenced entity or context.
-
C.
hasKeyQuestion
Indicates that one entity possesses or is associated with a primary or central question relevant to another entity.
-
D.
numberOfQueries
Indicates the total count of queries associated with or performed in a given context or entity.
-
E.
canAnswerQuestions
Indicates that an entity has the ability or capacity to respond correctly or appropriately to questions.
- 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_69c008ab9b3081908a11b2c744838435 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062443cec81909dc9bafea2f5e7d4 |
completed | March 22, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69c055fbce1081908805fd12e242ab96 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:19 p.m.