Triple
T31240644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny and the Deep Blue Sea |
E796549
|
entity |
| Predicate | hasMonologuesFor |
P111474
|
FINISHED |
| Object | male actors |
—
|
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: male actors | Statement: [Danny and the Deep Blue Sea, hasMonologuesFor, male actors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMonologuesFor Context triple: [Danny and the Deep Blue Sea, hasMonologuesFor, male actors]
-
A.
hasDialogueIn
Indicates that an entity participates in or contains spoken or written dialogue within a specified context, such as a scene, work, or medium.
-
B.
featuresMonologues
chosen
Indicates that something (such as a work, performance, or medium) contains or includes one or more monologues as a notable element.
-
C.
hasMultilingualDialogue
Indicates that an interaction or work contains dialogue expressed in more than one language.
-
D.
hasDialogueTrait
Indicates that an entity possesses a specific characteristic or quality related to dialogue or conversational behavior.
-
E.
hasWrittenDialogueFor
Indicates that one entity has created or authored dialogue content for another entity, such as a work, project, or production.
- 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_69f224db69ac81909a370adad6a7ac7c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
Created at: April 29, 2026, 9:11 p.m.