Triple
T26602173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dimasa Kachari |
E667663
|
entity |
| Predicate | traditionalDressMen |
P180767
|
FINISHED |
| Object | Sgaopha |
—
|
NE NERFINISHED |
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: Sgaopha | Statement: [Dimasa Kachari, traditionalDressMen, Sgaopha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalDressMen Context triple: [Dimasa Kachari, traditionalDressMen, Sgaopha]
-
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.
traditionalDressSimilarTo
Indicates that one traditional dress resembles or shares notable stylistic or cultural features with another traditional dress.
-
C.
traditionalDressColor
Indicates the color associated with an entity’s traditional or customary dress or clothing.
-
D.
nationalDress
Indicates that an item of clothing is recognized as the traditional or customary dress associated with a particular nation or culture.
-
E.
garmentType
Indicates the specific kind or category of garment associated with an entity.
- F. None of above. chosen
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_69ee9cfd20348190bb1255d2603efb7a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
| PDg | Predicate description generation | batch_69f7516c538481908c6e55cf76add098 |
completed | May 3, 2026, 1:45 p.m. |
Created at: April 27, 2026, 2:13 a.m.