Triple
T27937105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R.K. Maroon |
E700642
|
entity |
| Predicate | alignmentWithToons |
P163796
|
FINISHED |
| Object | exploitative |
—
|
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: exploitative | Statement: [R.K. Maroon, alignmentWithToons, exploitative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alignmentWithToons Context triple: [R.K. Maroon, alignmentWithToons, exploitative]
-
A.
alignmentComponents
Indicates that one entity is composed of or associated with specific subparts or elements that together form its overall alignment.
-
B.
alignmentWithProtagonist
Indicates the degree to which an entity’s goals, actions, or loyalties are supportive of, neutral toward, or opposed to the protagonist.
-
C.
alignmentShape
Indicates that one entity’s shape is arranged, oriented, or matched in position relative to another entity’s shape.
-
D.
alignmentWithMac
Indicates that something is compatible or properly configured to work with a Mac operating system or environment.
-
E.
alignmentInSeries
Indicates that one entity’s position or orientation is arranged in a specific way relative to others within an ordered sequence or series.
- F. None of above. chosen
Provenance (4 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_69ef6a5028108190a14696d9821dde49 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f63c045bd081908e0cb2a119202e8f |
completed | May 2, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69f6370ea79c81909b761821ee0fa698 |
completed | May 2, 2026, 5:40 p.m. |
| PDg | Predicate description generation | batch_69f63b3039808190b00bbd19161487f3 |
completed | May 2, 2026, 5:58 p.m. |
Created at: April 27, 2026, 7:14 p.m.