Triple
T270634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telnet |
E5624
|
entity |
| Predicate | usesEncoding |
P7661
|
FINISHED |
| Object | ASCII |
—
|
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: ASCII | Statement: [Telnet, usesEncoding, ASCII]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesEncoding Context triple: [Telnet, usesEncoding, ASCII]
-
A.
encodedIn
Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
-
B.
usesCharacterSet
chosen
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
C.
usesEncryptionAlgorithm
Indicates that one entity applies or relies on a specific encryption algorithm to protect data or communications.
-
D.
encodingBasisFor
Indicates that one encoding scheme serves as the foundational or reference basis for defining or interpreting another encoding.
-
E.
hasDigitalEncoding
Indicates that one entity is represented, stored, or expressed using a specific digital code or encoding scheme provided by another entity.
- 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25e69a9248190b9e7959b43223baa |
completed | Feb. 28, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69a25b721180819080d43c43fcbccf87 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.