Triple
T12009669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Layer Cake |
E285873
|
entity |
| Predicate | mainCharacterGoal |
P42284
|
FINISHED |
| Object | to retire from the drug trade |
—
|
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: to retire from the drug trade | Statement: [Layer Cake, mainCharacterGoal, to retire from the drug trade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterGoal Context triple: [Layer Cake, mainCharacterGoal, to retire from the drug trade]
-
A.
narrativeGoal
chosen
Indicates that one entity has a desired outcome or objective within a story or narrative context that drives their actions or development.
-
B.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
C.
protagonistAction
Indicates that the referenced entity performs the central or primary action associated with the main character in a narrative or scenario.
-
D.
initialGoal
Indicates that something represents the first or starting objective or target in a sequence of goals.
-
E.
goalDescription
Indicates that an entity expresses, specifies, or provides a textual description of a goal or intended outcome associated with another entity or activity.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903d61a4c81909e6cb6500b61df94 |
completed | April 10, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.