Triple
T4549736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sebastián Ramírez |
E110131
|
entity |
| Predicate | Typer |
P57939
|
FINISHED |
| Object | is a library for building CLI applications in Python |
—
|
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: is a library for building CLI applications in Python | Statement: [Sebastián Ramírez, Typer, is a library for building CLI applications in Python]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Typer Context triple: [Sebastián Ramírez, Typer, is a library for building CLI applications in Python]
-
A.
eraType
Indicates the classification of a time period or era according to its type or category.
-
B.
inker
Indicates that one entity serves as the inker for another, typically applying ink to finalize or enhance an existing drawing or artwork.
-
C.
ArchieType
Indicates a classification relationship where something is identified as an instance or example of a particular archetype or fundamental type.
-
D.
tartan
Indicates that something has a tartan pattern or is characterized by a tartan design.
-
E.
oreType
Indicates the specific kind or classification of ore associated with an 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57f3f8348190868e274ac4df87ce |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b4a9508190acdb888eef18f1ee |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:05 p.m.