Triple
T3250047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simple Speaks His Mind |
E68154
|
entity |
| Predicate | characterTypeOfSimple |
P10724
|
FINISHED |
| Object | working-class African American man |
—
|
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: working-class African American man | Statement: [Simple Speaks His Mind, characterTypeOfSimple, working-class African American man]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterTypeOfSimple Context triple: [Simple Speaks His Mind, characterTypeOfSimple, working-class African American man]
-
A.
hasTypicalCharacterType
chosen
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
-
B.
symbolType
Indicates the classification or category of a symbol based on its role, form, or function within a given system.
-
C.
characterSetType
Indicates the type or category of character set associated with or used by an entity.
-
D.
characterFunction
Indicates the role, purpose, or narrative function that a character serves within a story or context.
-
E.
textCharacter
Indicates that one entity is a character (such as a letter, digit, or symbol) within a piece of text associated with another entity.
- 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf40f7908190a450c3136fccb020 |
completed | March 8, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69ada41837e48190933572165be0ca38 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:09 p.m.