Triple
T38406611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Link |
E901346
|
entity |
| Predicate | originalClothing |
P204642
|
FINISHED |
| Object | animal skins |
—
|
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: animal skins | Statement: [Link, originalClothing, animal skins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalClothing Context triple: [Link, originalClothing, animal skins]
-
A.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
B.
traditionalClothingType
Indicates the type or category of traditional clothing associated with an entity.
-
C.
showsClothing
Indicates that one entity visually presents or displays an item of clothing associated with another entity.
-
D.
clothingPurpose
Indicates the functional role or intended use that a particular item of clothing serves (e.g., protection, fashion, uniform, sport).
-
E.
traditionalDressVariant
Indicates that one traditional dress is a variant or localized form of another traditional dress within the same broader cultural or stylistic tradition.
- 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_69f76e61e79c81908b787d83b46ab92b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:31 p.m.