Triple
T3884085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master of Suspense |
E92896
|
entity |
| Predicate | describesGenreSpecialization |
P21380
|
FINISHED |
| Object | thriller films |
—
|
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: thriller films | Statement: [Master of Suspense, describesGenreSpecialization, thriller films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesGenreSpecialization Context triple: [Master of Suspense, describesGenreSpecialization, thriller films]
-
A.
genreSpecialty
chosen
Indicates that an entity specializes in or is particularly associated with a specific genre.
-
B.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
-
C.
genreFeatures
Indicates that a particular genre is characterized or defined by certain features or attributes.
-
D.
depictsGenre
Indicates that one entity visually represents or portrays the genre category associated with another entity.
-
E.
hasSpecialty
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeec9029908190a7b36a3827734db1 |
completed | March 9, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69aee759609c8190985e96ec6d96dedd |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.