Triple
T36551071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shelob (film adaptations) |
E901257
|
entity |
| Predicate | visualDesignEmphasizes |
P65476
|
FINISHED |
| Object | size and grotesque realism |
—
|
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: size and grotesque realism | Statement: [Shelob (film adaptations), visualDesignEmphasizes, size and grotesque realism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualDesignEmphasizes Context triple: [Shelob (film adaptations), visualDesignEmphasizes, size and grotesque realism]
-
A.
designEmphasizes
chosen
Indicates that a design intentionally places special importance or focus on a particular feature, principle, or aspect over others.
-
B.
visualAppeal
Indicates that one entity finds another entity aesthetically pleasing or visually attractive.
-
C.
visualDesignInspiredBy
Indicates that the visual design of one entity is influenced, modeled, or derived from the visual style or appearance of another entity.
-
D.
visualImportance
Indicates how visually prominent or attention‑drawing one entity is relative to others in a given context.
-
E.
visualElements
Indicates that one entity contains, uses, or is characterized by specific visual components or graphical features associated with 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_69f76e61217081908b79d610fe67b013 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:11 p.m.