Triple
T19626799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanatana Goswami |
E471156
|
entity |
| Predicate | primarySubjectOfWritings |
P36841
|
FINISHED |
| Object | bhakti to Krishna |
—
|
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: bhakti to Krishna | Statement: [Sanatana Goswami, primarySubjectOfWritings, bhakti to Krishna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySubjectOfWritings Context triple: [Sanatana Goswami, primarySubjectOfWritings, bhakti to Krishna]
-
A.
literarySubject
chosen
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
B.
fieldOfWriting
Indicates that one entity is the domain, genre, or subject area in which another entity writes or produces written work.
-
C.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
D.
primarySubjectArea
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
-
E.
genreOfWorkContributedTo
Indicates that an entity contributed to a work belonging to a specified genre.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640eadcc48190ab5e36ddcde0c328 |
completed | April 20, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69e514e5cb108190ae260e466c447314 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.