Triple
T31907383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dishdasha |
E814589
|
entity |
| Predicate | wornInClimate |
P56311
|
FINISHED |
| Object | hot climate |
—
|
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: hot climate | Statement: [Dishdasha, wornInClimate, hot climate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wornInClimate Context triple: [Dishdasha, wornInClimate, hot climate]
-
A.
designedForClimate
chosen
Indicates that something has been intentionally created or adapted to function optimally under specific climate or environmental conditions.
-
B.
wornAt
Indicates that an item is being worn on a specific part of the body or at a particular time or event.
-
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.
wornOver
Indicates that one item of clothing or accessory is positioned on top of and covering another item when worn.
-
E.
wornInCountry
Indicates that an item of clothing or accessory is (or was) used or worn within a specified country.
- 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_69f348f04d7881909537fc9e7cbc670e |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b1b42d708190bd70ffd2ed7a1946 |
completed | May 3, 2026, 2:23 a.m. |
| PD | Predicate disambiguation | batch_69f6aca59d4881908d14ed47962703bd |
completed | May 3, 2026, 2:02 a.m. |
Created at: May 1, 2026, midnight