Triple
T24008026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivatans |
E594442
|
entity |
| Predicate | clothingPurpose |
P154842
|
FINISHED |
| Object | protection from sun |
—
|
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: protection from sun | Statement: [Ivatans, clothingPurpose, protection from sun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clothingPurpose Context triple: [Ivatans, clothingPurpose, protection from sun]
-
A.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
B.
colorOfApparel
Indicates the specific color attribute associated with a piece of apparel or clothing item.
-
C.
alsoWornIn
Indicates that an item of clothing or accessory is additionally worn in another context, location, or time beyond the primary one mentioned.
-
D.
clothingSymbolism
Indicates how clothing or attire conveys symbolic meaning, such as status, identity, emotion, or cultural significance, within a given context.
-
E.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
- 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_69e288bc8f608190ac4af29f0bd1c744 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d46ba1f88190a204d8cfb0f64be6 |
completed | April 29, 2026, 9:50 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 9:41 p.m.