Triple
T9853271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babla |
E239521
|
entity |
| Predicate | contributionToGenre |
P14417
|
FINISHED |
| Object | popularization of chutney as a distinct genre |
—
|
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: popularization of chutney as a distinct genre | Statement: [Babla, contributionToGenre, popularization of chutney as a distinct genre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contributionToGenre Context triple: [Babla, contributionToGenre, popularization of chutney as a distinct genre]
-
A.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
B.
influencedByGenre
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
C.
usedGenre
Indicates that one entity employs or is associated with a particular genre in its creation, presentation, or classification.
-
D.
workedOnGenre
chosen
Indicates that an entity (such as a person or organization) has done work related to a particular genre.
-
E.
genreSpecialty
Indicates that an entity specializes in or is particularly associated with a specific 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb376d32c819089381cf6ed83629d |
completed | April 2, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69cd03e57cac8190914bb5ae608a6e0e |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:34 p.m.