Triple
T4483760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Munster cheese |
E107185
|
entity |
| Predicate | typicalMoisture |
P42283
|
FINISHED |
| Object | high moisture content |
—
|
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: high moisture content | Statement: [Munster cheese, typicalMoisture, high moisture content]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMoisture Context triple: [Munster cheese, typicalMoisture, high moisture content]
-
A.
receivesMoistureFrom
Indicates that one entity obtains or is supplied with moisture (such as water, humidity, or precipitation) from another entity.
-
B.
wetnessLevel
chosen
Indicates the degree or intensity of how wet something is in relation to a reference state or scale.
-
C.
preferredHumidity
Indicates the level or range of humidity that is most suitable or favored by a given entity.
-
D.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
E.
typicalTexture
Indicates the usual or characteristic surface feel or consistency that is commonly associated with an entity.
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556d29f08190bab1e872dd7e819f |
completed | March 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69bd5213e3d0819094b026989e686f01 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 12:58 p.m.