Triple
T10172985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Malarkey |
E235777
|
entity |
| Predicate | genreOfWorkDepicting |
P41614
|
FINISHED |
| Object | war drama television miniseries |
—
|
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: war drama television miniseries | Statement: [Donald Malarkey, genreOfWorkDepicting, war drama television miniseries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfWorkDepicting Context triple: [Donald Malarkey, genreOfWorkDepicting, war drama television miniseries]
-
A.
genreOfWorkDirected
Indicates that a person has directed a work (such as a film, show, or performance) belonging to a specified genre.
-
B.
genreOfWorkActedIn
chosen
Indicates that an entity is the genre category of a work in which another entity performed or acted.
-
C.
genreOfProducedWorks
Indicates that one entity is the genre category to which the works produced by another entity belong.
-
D.
genreOfOriginWork
Indicates that a work is classified under a particular genre based on the genre of its original source work.
-
E.
genreOfWorkHonored
Indicates the specific genre or type of creative work for which an honor, award, or recognition is given.
- 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_69ca84d1d5f88190ab878a1021ecff68 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9f6dd8819081588600499165ee |
completed | April 2, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:10 p.m.