Triple
T8920964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cimbalom |
E212412
|
entity |
| Predicate | typicalMalletCovering |
P10512
|
FINISHED |
| Object | cotton or leather |
—
|
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: cotton or leather | Statement: [Cimbalom, typicalMalletCovering, cotton or leather]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMalletCovering Context triple: [Cimbalom, typicalMalletCovering, cotton or leather]
-
A.
hasCoverType
chosen
Indicates that one entity possesses or is associated with a specific type or category of cover.
-
B.
eraCovered
Indicates that one entity temporally encompasses, includes, or spans the historical period or era associated with another entity.
-
C.
surfaceCover
Indicates that one entity forms the material or layer that covers the outer surface of another entity.
-
D.
typicallyCovers
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses another entity.
-
E.
hasCoverings
Indicates that one entity possesses or is equipped with protective or enclosing layers, surfaces, or coverings provided by another 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_69ca839481d48190b42b037e0d0f636c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc665024f081909515e02e5f5b2221 |
completed | April 1, 2026, 12:26 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed0ef3c81908cc69eac852ee12a |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:56 p.m.