Triple
T26508530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vikata Kavi |
E669616
|
entity |
| Predicate | hasCanonicalNameInFolklore |
P105242
|
FINISHED |
| Object | Tenali Raman |
—
|
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: Tenali Raman | Statement: [Vikata Kavi, hasCanonicalNameInFolklore, Tenali Raman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCanonicalNameInFolklore Context triple: [Vikata Kavi, hasCanonicalNameInFolklore, Tenali Raman]
-
A.
hasNameInReligionOrFolklore
Indicates that an entity is known by a particular name specifically within a religious or folkloric tradition.
-
B.
hasFolkloreStatus
Indicates that something is recognized or classified as having a status or role within folklore or traditional cultural narratives.
-
C.
hasFullNameInCanon
Indicates that an entity’s complete, official name is explicitly established within the canonical source material.
-
D.
canonicallyReferredToAs
chosen
Indicates that one entity is the officially recognized or standard name or label by which another entity is known.
-
E.
hasMythologicalNamesake
Indicates that one entity is named after, or shares its name with, a figure or element from mythology.
- 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_69eeb319ec70819090834c2591cf5f1e |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 27, 2026, 1:18 a.m.