Triple
T5926798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chāndogya Upanishad |
E131831
|
entity |
| Predicate | containsMahavakya |
P1184
|
FINISHED |
| Object | Tat tvam asi |
—
|
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: Tat tvam asi | Statement: [Chāndogya Upanishad, containsMahavakya, Tat tvam asi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsMahavakya Context triple: [Chāndogya Upanishad, containsMahavakya, Tat tvam asi]
-
A.
associatedUpanishad
Indicates a relationship where something is linked or connected to a particular Upanishad as its source, reference, or context.
-
B.
hasBodhisattva
Indicates that one entity includes, is associated with, or is characterized by the presence or guidance of a bodhisattva.
-
C.
numberOfSutras
Indicates the quantity or count of sutras associated with a given entity.
-
D.
hasMatha
Indicates a relationship where one entity possesses, is associated with, or is characterized by a specific matha (monastic institution or religious seat).
-
E.
hasSacredText
chosen
Indicates that an entity possesses or is associated with a particular sacred or religious text.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4 p.m.