Triple
T27560337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pandoc |
E695751
|
entity |
| Predicate | canConvertBetween |
P14329
|
FINISHED |
| Object | Markdown and PDF |
—
|
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: Markdown and PDF | Statement: [Pandoc, canConvertBetween, Markdown and PDF]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canConvertBetween Context triple: [Pandoc, canConvertBetween, Markdown and PDF]
-
A.
allowsConversionTo
chosen
Indicates that one entity permits or enables transformation or change into another specified form or state.
-
B.
convertsTo
Indicates that one entity is transformed or changed into another entity, typically resulting in a different state, form, or representation.
-
C.
canTransform
Indicates that one entity is capable of being changed or converted into another entity or state.
-
D.
hasConversionIssueWith
Indicates that one entity experiences or is associated with a problem, error, or incompatibility when being converted to or from another entity.
-
E.
convertsFrom
Indicates that one entity is transformed or changed into another entity, with the source being the starting form or state.
- 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_69ef5387e97c8190a9dab040d21cd048 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 1:38 p.m.