Triple
T34254487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shadows (1922 film) |
E878832
|
entity |
| Predicate | leadCharacterEthnicityDepicted |
P28254
|
FINISHED |
| Object | Chinese |
—
|
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: Chinese | Statement: [Shadows (1922 film), leadCharacterEthnicityDepicted, Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterEthnicityDepicted Context triple: [Shadows (1922 film), leadCharacterEthnicityDepicted, Chinese]
-
A.
portrayedByEthnicity
Indicates that an entity is portrayed or represented by someone of a specified ethnic background.
-
B.
leadActorEthnicity
Indicates the ethnic background or identity of the primary (lead) actor in a work.
-
C.
protagonistEthnicity
chosen
Indicates the ethnic background or cultural heritage associated with a work’s main character.
-
D.
ethnicGroupDepicted
Indicates that a particular ethnic group is visually represented or portrayed in the subject entity (such as an image, artwork, or media item).
-
E.
hasEthnicityInFiction
Indicates that a fictional character or entity is portrayed as having a particular ethnicity within a narrative or fictional context.
- 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_69f349b421cc8190b4b4655e1d612548 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:56 a.m.