Triple
T4372467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toni Morrison bibliography |
E98928
|
entity |
| Predicate | focusesOnLanguage |
P56443
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Toni Morrison bibliography, focusesOnLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnLanguage Context triple: [Toni Morrison bibliography, focusesOnLanguage, English]
-
A.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
B.
languageShift
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
-
C.
primaryLanguageConcerned
Indicates that the relationship or action specifically involves or pertains to the main or principal language in question.
-
D.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
E.
otherLanguage
Indicates that an entity has or uses an additional language distinct from its primary or main language.
- 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_69b3454db3708190aeafd814413c4c3d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3521f7d9c81909c9209fe59d20ffd |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b35034cd248190bae09e9d090e13ec |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:17 p.m.