Triple
T14312093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rule 414 |
E354856
|
entity |
| Predicate | modeledWith |
P113729
|
FINISHED |
| Object | similar structure to Rule 413 |
—
|
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: similar structure to Rule 413 | Statement: [Rule 414, modeledWith, similar structure to Rule 413]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modeledWith Context triple: [Rule 414, modeledWith, similar structure to Rule 413]
-
A.
modeledBy
Indicates that one entity serves as a model or representation of another, typically capturing its structure, behavior, or properties.
-
B.
hasModelledFor
Indicates that one entity has served as a model for another entity, typically in a professional or representational context such as art, photography, or fashion.
-
C.
adoptedModel
Indicates that one entity has formally chosen, accepted, or implemented another entity as its preferred model or standard.
-
D.
possibleModel
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
E.
isModelOf
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b386d0819087d14f3ce84a1997 |
completed | April 14, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a8f81f08190af737e1654847aa6 |
completed | April 14, 2026, 11:52 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:12 a.m.