Triple
T27005178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agonshu |
E680221
|
entity |
| Predicate | coreTextFocus |
P142680
|
FINISHED |
| Object | Agama sutras |
—
|
NE NERFINISHED |
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: Agama sutras | Statement: [Agonshu, coreTextFocus, Agama sutras]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coreTextFocus Context triple: [Agonshu, coreTextFocus, Agama sutras]
-
A.
coreText
Indicates that something serves as the main or primary textual content within a larger work or context.
-
B.
canonicalFocus
Indicates that one entity is the primary or most representative focus or point of attention in relation to another entity.
-
C.
hasFocusText
chosen
Indicates that one entity provides the primary or highlighted textual content associated with another entity.
-
D.
primaryTextualFocus
Indicates that one entity is the main subject or central topic emphasized within the text of another entity.
-
E.
importFocus
Indicates that attention, priority, or emphasis is being brought into or concentrated on a particular entity or aspect.
- 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_69eeeb53939c8190bd431f32b060f01f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 7 a.m.