Triple
T35808586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Viper |
E1035166
|
entity |
| Predicate | visualMannerism |
P132102
|
FINISHED |
| Object | snake-like crawl |
—
|
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: snake-like crawl | Statement: [The Viper, visualMannerism, snake-like crawl]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualMannerism Context triple: [The Viper, visualMannerism, snake-like crawl]
-
A.
visualAppeal
Indicates that one entity finds another entity aesthetically pleasing or visually attractive.
-
B.
visuallyDefines
Indicates that one entity establishes or clarifies the appearance, form, or visual characteristics of another entity.
-
C.
visualConvention
Indicates a conventional or commonly accepted way of visually representing or depicting something, rather than a literal or unique visual form.
-
D.
visualDetail
chosen
Indicates that one entity provides or specifies the visual characteristics, features, or appearance details of another entity.
-
E.
visualWorkFor
Indicates a relationship where one entity creates, designs, or produces visual material (such as graphics, images, or visual assets) specifically for another entity or purpose.
- 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_69f76e1762408190b885a8456862e372 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.