Triple
T932881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atharvaveda |
E20131
|
entity |
| Predicate | textualStructure |
P22618
|
FINISHED |
| Object | collection of books |
—
|
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: collection of books | Statement: [Atharvaveda, textualStructure, collection of books]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textualStructure Context triple: [Atharvaveda, textualStructure, collection of books]
-
A.
textType
Indicates the classification of a text according to its type, format, or genre.
-
B.
grammaticalStructure
Indicates the way linguistic elements are organized and related within a sentence or phrase according to grammatical rules.
-
C.
structureStyle
Indicates the architectural or design style characterizing how a structure is built or formed.
-
D.
textFragment
Indicates that one piece of text is a constituent part or segment of a larger text.
-
E.
segmentStructure
Indicates that one entity represents a structural or organizational subdivision (a segment) within the overall structure of another entity.
- F. None of above. chosen
Provenance (4 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3bcad2481908b83575b2fb80d14 |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b299c4d881908a57ac2711676cd7 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b3bab5788190a62a0e23a698f7c7 |
completed | March 1, 2026, 9:46 p.m. |
Created at: March 1, 2026, 7:40 p.m.