Triple
T22029951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banquo’s ghost banquet scene |
E544057
|
entity |
| Predicate | LadyMacbethAction |
P135178
|
FINISHED |
| Object | attempts to excuse Macbeth’s behavior |
—
|
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: attempts to excuse Macbeth’s behavior | Statement: [Banquo’s ghost banquet scene, LadyMacbethAction, attempts to excuse Macbeth’s behavior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LadyMacbethAction Context triple: [Banquo’s ghost banquet scene, LadyMacbethAction, attempts to excuse Macbeth’s behavior]
-
A.
famousPlay
Indicates that the subject is a well-known or widely recognized theatrical play.
-
B.
dramaticAction
chosen
Indicates an action or event characterized by heightened emotion, tension, or significance that drives or intensifies a dramatic situation or narrative.
-
C.
typeOfPlay
Indicates the specific category or genre of a play that characterizes what kind of play it is.
-
D.
hasHamlet
Indicates that an entity possesses, contains, or is associated with a hamlet (a small settlement).
-
E.
dramatises
Indicates that one entity presents, adapts, or portrays the events, themes, or content of another entity in a dramatic or theatrical form.
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127ed0cb08190aead0838cc62934c |
completed | April 28, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69e6f63b0d048190b241622759aab9de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:24 p.m.