Triple
T5163734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Sea Hawk (1924 film) |
E116497
|
entity |
| Predicate | hasSourceMaterialGenre |
P61875
|
FINISHED |
| Object | historical adventure novel |
—
|
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: historical adventure novel | Statement: [The Sea Hawk (1924 film), hasSourceMaterialGenre, historical adventure novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSourceMaterialGenre Context triple: [The Sea Hawk (1924 film), hasSourceMaterialGenre, historical adventure novel]
-
A.
hasGenreOrigin
Indicates that a genre originates from, or has its roots in, a particular source, place, culture, or tradition.
-
B.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
C.
hasMainGenre
Indicates that an entity’s primary or most characteristic genre is the specified genre.
-
D.
hasGenreArtist
Indicates that an artist is associated with or specializes in a particular genre.
-
E.
hasGenreStrength
Indicates that something possesses a particular intensity or degree of emphasis associated with a specific genre.
- F. None of above. chosen
Provenance (4 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_69bd445edb3881909b93b34d260717fc |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7927a348819082ad531955cdf30d |
completed | March 20, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69bd77b36c008190b91011a9fa52b3d2 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd78d6a1388190804dcf568ca92129 |
completed | March 20, 2026, 4:41 p.m. |
Created at: March 20, 2026, 1:44 p.m.