Triple
T2261629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muscadelle |
E50051
|
entity |
| Predicate | clusterCharacteristics |
P12090
|
FINISHED |
| Object | compact grape clusters |
—
|
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: compact grape clusters | Statement: [Muscadelle, clusterCharacteristics, compact grape clusters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clusterCharacteristics Context triple: [Muscadelle, clusterCharacteristics, compact grape clusters]
-
A.
clusterDensity
chosen
Indicates the degree to which elements within a cluster are closely packed or concentrated relative to its size or volume.
-
B.
membershipCharacteristic
Indicates that an entity possesses a specific attribute or quality by virtue of its membership in a particular group or category.
-
C.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
D.
demographicsCharacteristic
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
-
E.
rankFunctionCharacterization
Indicates that a function is being characterized or defined in terms of its rank, typically specifying how the rank property determines or describes the function’s behavior or classification.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc2ea65288190bc8644a07a11dfa9 |
completed | March 7, 2026, 6:17 a.m. |
| PD | Predicate disambiguation | batch_69abbdb592588190ac1ef5e8c54575b1 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.