Triple
T16785818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fatal Hour |
E407969
|
entity |
| Predicate | portraysEthnicityOfDetective |
P28254
|
FINISHED |
| Object | Chinese-American |
—
|
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-American | Statement: [The Fatal Hour, portraysEthnicityOfDetective, Chinese-American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysEthnicityOfDetective Context triple: [The Fatal Hour, portraysEthnicityOfDetective, Chinese-American]
-
A.
portrayedDetective
Indicates that one entity has played or depicted a detective character in a performance or work.
-
B.
portrayedByEthnicity
Indicates that an entity is portrayed or represented by someone of a specified ethnic background.
-
C.
detectiveType
Indicates that one entity is classified as a particular type or category of detective in relation to another entity.
-
D.
protagonistEthnicity
chosen
Indicates the ethnic background or cultural heritage associated with a work’s main character.
-
E.
hasFictionalDetective
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b21a52ac8190b4374aa0fc45683a |
completed | April 18, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.