Triple
T32133773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parbatiya |
E820716
|
entity |
| Predicate | associatedWithDress |
P27860
|
FINISHED |
| Object | Daura Suruwal |
E1070823
|
NE 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: Daura Suruwal | Statement: [Parbatiya, associatedWithDress, Daura Suruwal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithDress Context triple: [Parbatiya, associatedWithDress, Daura Suruwal]
-
A.
usesDressing
Indicates that one entity applies or employs a particular dressing (such as a sauce, covering, or treatment) in relation to another entity or context.
-
B.
typicallyWornWith
chosen
Indicates that one item of clothing or accessory is commonly or customarily worn together with another.
-
C.
associatedWithFashion
Indicates a relationship where something is connected or related to fashion, style, or the fashion industry in some meaningful way.
-
D.
alsoWornIn
Indicates that an item of clothing or accessory is additionally worn in another context, location, or time beyond the primary one mentioned.
-
E.
dressFeature
Indicates that a dress possesses or is characterized by a particular feature, attribute, or design element.
- F. None of above.
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_69f349039e0c819091c7a7d322e3f46d |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2f0138dd18819099b6cf8177ed7ea6 |
completed | June 14, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:30 a.m.