Triple
T150310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toni Morrison |
E3415
|
entity |
| Predicate | writingTheme |
P261
|
FINISHED |
| Object | Black American life |
—
|
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: Black American life | Statement: [Toni Morrison, writingTheme, Black American life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingTheme Context triple: [Toni Morrison, writingTheme, Black American life]
-
A.
wrote
Indicates that an entity is the author or creator of a written work involving another entity.
-
B.
theme
chosen
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
C.
rite
Indicates a ceremonial or ritual action performed according to established traditions or religious practices.
-
D.
typingDiscipline
Indicates how a programming language enforces and manages type rules for its values and expressions.
-
E.
writtenForm
Indicates that one entity is the textual or orthographic representation (spelling or written version) of 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580dda148190a522e0ac276d5f33 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a256599db08190a7b000b381d32ec4 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.