Triple
T21108380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saida Khera |
E520110
|
entity |
| Predicate | hasFolkloreStatus |
P142887
|
FINISHED |
| Object | legendary love story setting |
—
|
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: legendary love story setting | Statement: [Saida Khera, hasFolkloreStatus, legendary love story setting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFolkloreStatus Context triple: [Saida Khera, hasFolkloreStatus, legendary love story setting]
-
A.
includesFolklore
Indicates that one entity contains, incorporates, or features folklore as part of its content or composition.
-
B.
hasFolkTaleType
Indicates that an entity (such as a story) is classified as belonging to a particular folk tale type or category.
-
C.
hasMythologicalBasis
Indicates that something is founded on, derived from, or significantly influenced by a mythological story, figure, or tradition.
-
D.
hasEthnographicStatus
Indicates that an entity is associated with a particular ethnographic classification, status, or role within a cultural or social context.
-
E.
countryOfFolklore
Indicates the country with which a particular piece or tradition of folklore is associated or from which it originates.
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e720ffa998819082db225363ac3b23 |
completed | April 21, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69e5dbff56848190a03b350a9305c612 |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2e03d88819086f8b641656ad8b0 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:54 p.m.