Triple
T4781876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taittiriya Shakha |
E106384
|
entity |
| Predicate | textualLayer |
P11293
|
FINISHED |
| Object | Samhita layer |
—
|
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: Samhita layer | Statement: [Taittiriya Shakha, textualLayer, Samhita layer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textualLayer Context triple: [Taittiriya Shakha, textualLayer, Samhita layer]
-
A.
textualStructure
Indicates how parts of a text are organized and related to each other within its overall structure.
-
B.
coreText
chosen
Indicates that something serves as the main or primary textual content within a larger work or context.
-
C.
textType
Indicates the classification of a text according to its type, format, or genre.
-
D.
textContent
Indicates that one entity is the textual content or written material contained within another entity.
-
E.
textMode
Indicates that something operates, is displayed, or is processed in a mode where information is handled primarily as text rather than as graphics or other media.
- 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_69bd43f4a9588190bf73e20bc27c03cc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd69237f80819090713ed62653fb75 |
completed | March 20, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69bd622be1388190ab5511b589c878c0 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:22 p.m.