Triple
T33761765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skolem arithmetic |
E865123
|
entity |
| Predicate | hasModels |
P197425
|
FINISHED |
| Object | standard model (ℕ, ×) |
—
|
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: standard model (ℕ, ×) | Statement: [Skolem arithmetic, hasModels, standard model (ℕ, ×)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModels Context triple: [Skolem arithmetic, hasModels, standard model (ℕ, ×)]
-
A.
hasModelSeries
Indicates a relationship where an item or product is associated with a specific model series it belongs to.
-
B.
hasModelStatus
Indicates that an entity is assigned a particular model-related state or condition, such as its current phase, validity, or operational status within a modeling context.
-
C.
numberOfModels
Indicates the quantity or count of models associated with a given entity or context.
-
D.
usesModelsType
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
-
E.
hadModel
Indicates that an entity possessed, used, or was associated with a particular model (e.g., a product, design, or version) at some point in time.
- F. None of above. chosen
Provenance (4 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_69f3498d3b748190aa3c4006c1f32f38 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe91383a1c81909266e40c3c3ede6c |
completed | May 9, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69fe8fde094081908f0f121664fbb5c7 |
completed | May 9, 2026, 1:37 a.m. |
| PDg | Predicate description generation | batch_69fe9137730c81909d1d57c30566c89a |
completed | May 9, 2026, 1:43 a.m. |
Created at: May 1, 2026, 1:45 a.m.