Triple
T8035660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TIE Echelon |
E187099
|
entity |
| Predicate | visualMedium |
P80689
|
FINISHED |
| Object | live-action theme park environment |
—
|
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: live-action theme park environment | Statement: [TIE Echelon, visualMedium, live-action theme park environment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualMedium Context triple: [TIE Echelon, visualMedium, live-action theme park environment]
-
A.
visualElements
Indicates that one entity contains, uses, or is characterized by specific visual components or graphical features associated with another entity.
-
B.
mediaDepictionAs
Indicates that one entity is portrayed or represented as another entity or in a particular way within some medium (e.g., image, film, text).
-
C.
visualCompanion
Indicates that one entity serves as a visual counterpart, partner, or accompanying element to another in a visual context.
-
D.
depictsMedium
Indicates that one entity visually represents or portrays the medium or material of another entity.
-
E.
mediaAssets
Indicates a relationship where one entity is associated with one or more media-related resources or files (such as images, videos, or audio).
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ef68c6081908727d17238b3522a |
completed | March 31, 2026, 3:26 a.m. |
| PD | Predicate disambiguation | batch_69cb049688208190b32088bd2c5930bc |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bcbbc0819094a98e7ffffb7a40 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:22 p.m.