Triple
T27509751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playfair cipher |
E694375
|
entity |
| Predicate | typicalFillerLetter |
P200937
|
FINISHED |
| Object | X |
—
|
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: X | Statement: [Playfair cipher, typicalFillerLetter, X]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFillerLetter Context triple: [Playfair cipher, typicalFillerLetter, X]
-
A.
letterType
Indicates the specific category or kind of letter associated with or assigned to an entity.
-
B.
letter3
Indicates that one entity is the third letter (or character) of another entity, typically a string or word.
-
C.
chairLetter
Indicates that an entity serves as the chair or lead signatory of a particular letter or written communication.
-
D.
openingLetters
Indicates that one entity is the initial or first letter(s) of another entity (such as a word, name, or string).
-
E.
letterer
Indicates that one entity serves as the letterer of another, typically responsible for drawing or designing the lettering (such as text or captions) in that work.
- 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_69ef53842afc8190ba6bd4e4999bda67 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69ffbb1c5bf88190a0bf791213045885 |
completed | May 9, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69ffba0ab0f881908f84ef81f7a1bfe8 |
completed | May 9, 2026, 10:49 p.m. |
| PDg | Predicate description generation | batch_69ffbb1b3b888190ba329ad321fc3f3d |
completed | May 9, 2026, 10:54 p.m. |
Created at: April 27, 2026, 1:15 p.m.