Triple
T4575451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTF-7 |
E123130
|
entity |
| Predicate | encodesDirectly |
P58055
|
FINISHED |
| Object | subset of ASCII characters |
—
|
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: subset of ASCII characters | Statement: [UTF-7, encodesDirectly, subset of ASCII characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encodesDirectly Context triple: [UTF-7, encodesDirectly, subset of ASCII characters]
-
A.
encodes
Indicates that one entity contains or represents the information, instructions, or structure of another in a coded or symbolic form.
-
B.
encodingBasisFor
Indicates that one encoding scheme serves as the foundational or reference basis for defining or interpreting another encoding.
-
C.
encodedIn
Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
-
D.
encodedInUnicodeSince
Indicates that a given character or symbol has been included and assigned a code point in the Unicode standard starting from a specific version or time.
-
E.
dataEncodingMethod
Indicates the specific technique or format used to encode data for storage, transmission, or processing.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58dfe3508190b21836079e951a3c |
completed | March 20, 2026, 2:25 p.m. |
| PD | Predicate disambiguation | batch_69bd5228b70c8190ac48705e35a710c1 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b4a9508190acdb888eef18f1ee |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:10 p.m.