Triple
T28609065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EncFS |
E724126
|
entity |
| Predicate | reverseModeDescription |
P164908
|
FINISHED |
| Object | encrypts a plaintext directory into an encrypted view |
—
|
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: encrypts a plaintext directory into an encrypted view | Statement: [EncFS, reverseModeDescription, encrypts a plaintext directory into an encrypted view]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reverseModeDescription Context triple: [EncFS, reverseModeDescription, encrypts a plaintext directory into an encrypted view]
-
A.
reverseFeature
Indicates that one feature is the inverse or opposite counterpart of another feature in a given context.
-
B.
reversed
Indicates that the direction or order of a previously defined relationship or sequence between entities is inverted.
-
C.
mayReverse
Indicates that an action, process, or state can be undone or returned to a previous condition.
-
D.
typicalReverseType
Indicates that the subject is the usual or canonical inverse relation type of the given predicate.
-
E.
reverseMotif
Indicates that one motif is the reversed or inverted form of another motif in structure, order, or direction.
- 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651aad92c8190b874b3b5f9f64434 |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f652a3a8208190a4fdd66f34138bd2 |
completed | May 2, 2026, 7:38 p.m. |
Created at: April 28, 2026, 4:29 a.m.