Triple
T6254459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banarasi saris |
E140126
|
entity |
| Predicate | palluStyle |
P68143
|
FINISHED |
| Object | heavily decorated pallu |
—
|
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: heavily decorated pallu | Statement: [Banarasi saris, palluStyle, heavily decorated pallu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: palluStyle Context triple: [Banarasi saris, palluStyle, heavily decorated pallu]
-
A.
poloStyle
Indicates a stylistic relationship where one entity is characterized by or associated with a particular style of polo.
-
B.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
-
C.
fashionCharacteristic
chosen
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
D.
styleCategory
Indicates the stylistic classification or genre category that an item, work, or entity belongs to.
-
E.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
- 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_69c008b4858c819095b0199114a9a87b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063625608819081f5422112c80ce5 |
completed | March 22, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69c05605566c81908e197f5accd072d2 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:24 p.m.