Triple
T32499397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Chan film series |
E830611
|
entity |
| Predicate | hasPortrayalIssues |
P197742
|
FINISHED |
| Object | racial stereotyping |
—
|
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: racial stereotyping | Statement: [Charlie Chan film series, hasPortrayalIssues, racial stereotyping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPortrayalIssues Context triple: [Charlie Chan film series, hasPortrayalIssues, racial stereotyping]
-
A.
hasPortrayalQuality
Indicates that something possesses a particular characteristic or standard of quality in how it is portrayed or represented.
-
B.
hasScreenPortrayal
Indicates that an entity is depicted or represented by a specific on-screen performance or portrayal, such as in film, television, or other visual media.
-
C.
challengesPortrayalOf
Indicates that one entity questions, disputes, or undermines the way another entity is represented or depicted.
-
D.
hasColorIssues
Indicates that an entity exhibits problems, defects, or inconsistencies related to its color or coloration.
-
E.
hasBodyImageIssue
Indicates that an entity experiences concerns, dissatisfaction, or negative perceptions about their own body or physical appearance.
- 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_69f349219cb8819087e120f509629c1b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fea5e828cc8190a9b755a645dc56d2 |
completed | May 9, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69fea36443f08190b2aced9b4a0525fd |
completed | May 9, 2026, 3 a.m. |
| PDg | Predicate description generation | batch_69fea5e75a5481908a04d91ee7255ebb |
completed | May 9, 2026, 3:11 a.m. |
Created at: May 1, 2026, 12:59 a.m.