Triple
T6322789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickey Pearson |
E141782
|
entity |
| Predicate | goalInStory |
P42284
|
FINISHED |
| Object | to sell his cannabis empire profitably |
—
|
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 sell his cannabis empire profitably | Statement: [Mickey Pearson, goalInStory, to sell his cannabis empire profitably]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goalInStory Context triple: [Mickey Pearson, goalInStory, to sell his cannabis empire profitably]
-
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.
goalDescription
Indicates that an entity expresses, specifies, or provides a textual description of a goal or intended outcome associated with another entity or activity.
-
C.
goals
Indicates that an entity has objectives, targets, or desired outcomes it aims to achieve.
-
D.
goalStructure
Indicates the overarching objective or intended outcome that organizes and guides the structure of related actions, components, or relationships.
-
E.
gameObjective
Indicates the primary goal or intended outcome that participants aim to achieve within a game.
- 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_69c008d201748190917e69c41ba3f978 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064e38f1c81909c7e90b520602bae |
completed | March 22, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69c060e5efc48190861b8266e5b0cc0c |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:29 p.m.