Triple
T902450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upanishads |
E19475
|
entity |
| Predicate | numberOfPrincipalTexts |
P11803
|
FINISHED |
| Object | 13 (commonly recognized principal Upanishads) |
—
|
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: 13 (commonly recognized principal Upanishads) | Statement: [Upanishads, numberOfPrincipalTexts, 13 (commonly recognized principal Upanishads)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPrincipalTexts Context triple: [Upanishads, numberOfPrincipalTexts, 13 (commonly recognized principal Upanishads)]
-
A.
numberOfEssays
Indicates the quantity of essays associated with a given entity or context.
-
B.
numberOfWorks
Indicates the total count of works associated with a given entity.
-
C.
numberOfConstituents
Indicates the total count of individual components or members that make up a larger whole or group.
-
D.
approximateNumberOfTractates
chosen
Indicates a relationship where an entity is associated with an estimated or non-exact count of tractates linked to it.
-
E.
numberOfStories
Indicates the total count of levels or floors that a structure or building has.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad56f4c08190a7a5091ff0eb3209 |
completed | March 1, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69a4aa98caec8190bbcc38320090f058 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.