Triple
T27509750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playfair cipher |
E694375
|
entity |
| Predicate | plaintextPreprocessing |
P125172
|
FINISHED |
| Object | pad final single letter with filler |
—
|
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: pad final single letter with filler | Statement: [Playfair cipher, plaintextPreprocessing, pad final single letter with filler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plaintextPreprocessing Context triple: [Playfair cipher, plaintextPreprocessing, pad final single letter with filler]
-
A.
textProcessing
chosen
Indicates the action of analyzing, transforming, or manipulating text data to extract information, modify its form, or prepare it for further use.
-
B.
plaintextType
Indicates that the associated content or data is represented in an unencrypted, human-readable text format.
-
C.
preDraftProcess
Indicates the procedural steps or activities that occur before a draft is created or formally written.
-
D.
pretext
Indicates that one party uses a stated reason or excuse to conceal their true motive for an action or decision.
-
E.
pretrainingTask
Indicates that an entity is used as a training objective or learning activity applied to another entity during a model’s pretraining phase.
- 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_69ef53842afc8190ba6bd4e4999bda67 |
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, 1:15 p.m.