Triple
T13460868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | shalwar kameez |
E311358
|
entity |
| Predicate | typicalLengthOfKameez |
P18065
|
FINISHED |
| Object | knee-length |
—
|
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: knee-length | Statement: [shalwar kameez, typicalLengthOfKameez, knee-length]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLengthOfKameez Context triple: [shalwar kameez, typicalLengthOfKameez, knee-length]
-
A.
typicalLength
chosen
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
B.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
C.
typicalHemlineLength
Indicates the usual or characteristic length of the hemline associated with an item, style, or category of clothing.
-
D.
traditionalDressVariant
Indicates that one traditional dress is a variant or localized form of another traditional dress within the same broader cultural or stylistic tradition.
-
E.
properLengthMeasuredIn
Indicates that the proper (intrinsic or rest-frame) length of an entity is expressed using a specified unit of measurement.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf0c177081909178dec61b09c278 |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69d9a03dcd0c8190a8927eb4eaad1c45 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:41 p.m.