Triple
T1833151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward Linden |
E41003
|
entity |
| Predicate | hasNotableStyle |
P1609
|
FINISHED |
| Object | special-effects-oriented cinematography |
—
|
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: special-effects-oriented cinematography | Statement: [Edward Linden, hasNotableStyle, special-effects-oriented cinematography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableStyle Context triple: [Edward Linden, hasNotableStyle, special-effects-oriented cinematography]
-
A.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
B.
hasStyle
chosen
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
C.
hasNotableGenre
Indicates that an entity is significantly associated with a particular genre, such that the genre is especially characteristic or noteworthy for that entity.
-
D.
hasContractStyle
Indicates that one entity is associated with or characterized by a particular contract style or contractual format.
-
E.
notableWorkStyle
Indicates a stylistic characteristic or distinctive manner associated with a notable work created by the subject.
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafd88ebc81908208394746351fe6 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.