Triple
T36490391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Model To Learn Them All |
E899035
|
entity |
| Predicate | typeOfArchitecture |
P4631
|
FINISHED |
| Object | unified model |
—
|
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: unified model | Statement: [One Model To Learn Them All, typeOfArchitecture, unified model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfArchitecture Context triple: [One Model To Learn Them All, typeOfArchitecture, unified model]
-
A.
architectureType
chosen
Indicates the specific style or category of architecture that characterizes or defines an entity.
-
B.
exampleArchitecture
Indicates that one entity serves as a representative or illustrative instance of the architectural style, structure, or design of another entity.
-
C.
architectureName
Indicates the specific name or title assigned to an architecture.
-
D.
architecturalConcept
Indicates that one entity represents or embodies an architectural concept in relation to another entity.
-
E.
architecturalWorkType
Indicates the specific kind or category of architectural work that characterizes the relationship between entities.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a030d3db2748190b32fcf7b21bd0d0a |
completed | May 12, 2026, 11:21 a.m. |
| PD | Predicate disambiguation | batch_6a030ca6bf388190b2f6931376323da3 |
completed | May 12, 2026, 11:19 a.m. |
Created at: May 3, 2026, 4:10 p.m.