Triple
T7045127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onam |
E163611
|
entity |
| Predicate | dressTradition |
P42256
|
FINISHED |
| Object | wearing traditional Kerala attire |
—
|
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: wearing traditional Kerala attire | Statement: [Onam, dressTradition, wearing traditional Kerala attire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dressTradition Context triple: [Onam, dressTradition, wearing traditional Kerala attire]
-
A.
traditionalDressVariant
Indicates that one traditional dress is a variant or localized form of another traditional dress within the same broader cultural or stylistic tradition.
-
B.
traditionalPilgrimAttire
Indicates that an entity is wearing or associated with clothing customarily worn by pilgrims in a particular cultural or religious tradition.
-
C.
clothingSymbolism
Indicates how clothing or attire conveys symbolic meaning, such as status, identity, emotion, or cultural significance, within a given context.
-
D.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
E.
fashionStyle
chosen
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
- 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_69c6885f598c8190b6b6495c59d8d962 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bb602081908bfa6186a1f5a4b4 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:37 p.m.