Triple
T9540057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Moto film series |
E230127
|
entity |
| Predicate | hasProtagonistEthnicityDepiction |
P28254
|
FINISHED |
| Object | Asian detective |
—
|
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: Asian detective | Statement: [Mr. Moto film series, hasProtagonistEthnicityDepiction, Asian detective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProtagonistEthnicityDepiction Context triple: [Mr. Moto film series, hasProtagonistEthnicityDepiction, Asian detective]
-
A.
protagonistEthnicity
chosen
Indicates the ethnic background or cultural heritage associated with a work’s main character.
-
B.
portrayedByEthnicity
Indicates that an entity is portrayed or represented by someone of a specified ethnic background.
-
C.
hasEthnicCharacteristic
Indicates that an entity possesses or is associated with a particular ethnic characteristic or identity.
-
D.
leadActorEthnicity
Indicates the ethnic background or identity of the primary (lead) actor in a work.
-
E.
depictsEthnicContext
Indicates that one entity visually represents or portrays the ethnic background, identity, or cultural context 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e4df6c8190a4d1160c42daa45f |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:01 p.m.