Triple
T35097506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minimundus |
E1012904
|
entity |
| Predicate | modelMaterial |
P92637
|
FINISHED |
| Object | original materials where possible |
—
|
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: original materials where possible | Statement: [Minimundus, modelMaterial, original materials where possible]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelMaterial Context triple: [Minimundus, modelMaterial, original materials where possible]
-
A.
exampleMaterial
Indicates that something serves as a representative or illustrative material or sample of something else.
-
B.
matrixMaterial
Indicates that one material serves as the continuous matrix phase in which another component or reinforcement is embedded.
-
C.
materialParameter
Indicates a relationship where a specific parameter or property is associated with, or characterizes, a material in a given context.
-
D.
materialOptions
chosen
Indicates that there are one or more possible materials that can be chosen or applied in relation to a given entity or context.
-
E.
material
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other 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_69f76dd556248190808b4c4f43debebb |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.