Triple
T31803957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deglet Nour |
E811817
|
entity |
| Predicate | hasTypicalMoistureClass |
P145866
|
FINISHED |
| Object | semi-dry |
—
|
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: semi-dry | Statement: [Deglet Nour, hasTypicalMoistureClass, semi-dry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalMoistureClass Context triple: [Deglet Nour, hasTypicalMoistureClass, semi-dry]
-
A.
hasMoistureRegime
Indicates a relationship where an entity is characterized by a specific pattern or condition of moisture availability (e.g., wetness, dryness, or seasonal water regime).
-
B.
typicalMoistureContent
chosen
Indicates the usual or characteristic amount of moisture present in or associated with an entity under normal conditions.
-
C.
isMoistureSensitive
Indicates that the entity is susceptible to damage, degradation, or altered performance when exposed to moisture or humidity.
-
D.
hasHumidity
Indicates that one entity possesses, exhibits, or is characterized by a certain level or measure of humidity.
-
E.
wetnessLevel
Indicates the degree or intensity of how wet something is in relation to a reference state or scale.
- 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_69f348e70d188190b4637c5509f81274 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fea5e828cc8190a9b755a645dc56d2 |
completed | May 9, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69fea36443f08190b2aced9b4a0525fd |
completed | May 9, 2026, 3 a.m. |
Created at: April 30, 2026, 11:42 p.m.