Triple
T33609475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Money Trees |
E860949
|
entity |
| Predicate | hasRecurrentMotive |
P112503
|
FINISHED |
| Object | pursuit of money as salvation |
—
|
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: pursuit of money as salvation | Statement: [Money Trees, hasRecurrentMotive, pursuit of money as salvation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurrentMotive Context triple: [Money Trees, hasRecurrentMotive, pursuit of money as salvation]
-
A.
repeatedMotive
chosen
Indicates that the same motive recurs multiple times within a work, sequence, or context.
-
B.
hasRecurringActor
Indicates that an actor appears repeatedly across multiple instances or episodes within a work or series.
-
C.
hasMotiveContext
Indicates that there is contextual information explaining the reasons or motivations behind an action, event, or relationship.
-
D.
hasMotiveElement
Indicates that one entity includes, specifies, or is characterized by a particular motive-related component or factor in a broader relationship or action.
-
E.
hasMotiveOfCriminals
Indicates that the specified motive is attributed to or associated with the criminals in question.
- 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_69f3498037c88190a4500f002b5540e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:41 a.m.