Triple
T4424853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLIP |
E95184
|
entity |
| Predicate | textEncoderType |
P55911
|
FINISHED |
| Object | Transformer |
—
|
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: Transformer | Statement: [CLIP, textEncoderType, Transformer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textEncoderType Context triple: [CLIP, textEncoderType, Transformer]
-
A.
textType
Indicates the classification of a text according to its type, format, or genre.
-
B.
codingSystemType
Indicates the classification or category of coding system used to encode or represent information in a given context.
-
C.
textMode
Indicates that something operates, is displayed, or is processed in a mode where information is handled primarily as text rather than as graphics or other media.
-
D.
textCharacter
Indicates that one entity is a character (such as a letter, digit, or symbol) within a piece of text associated with another entity.
-
E.
encodes
Indicates that one entity contains or represents the information, instructions, or structure of another in a coded or symbolic form.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3554ca5208190ba2661616dcf071c |
completed | March 13, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69b34f5eabe88190a12b244ea71e46d6 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3505a87b4819083fbbd58870e520b |
completed | March 12, 2026, 11:46 p.m. |
Created at: March 12, 2026, 11:30 p.m.