Triple
T912144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Example |
E19682
|
entity |
| Predicate | nationalityOfAuthor |
P6689
|
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: [The Example, nationalityOfAuthor, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityOfAuthor Context triple: [The Example, nationalityOfAuthor, English]
-
A.
authorNationality
chosen
Indicates the relationship between an author and the country or nationality with which that author is identified.
-
B.
nationalityInStory
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
C.
creatorNationality
Indicates that the creator of an entity has a specified national affiliation or citizenship.
-
D.
associatedComposerNationality
Indicates that there is a relationship between a composer and a specific nationality with which that composer is identified or associated.
-
E.
brandNationality
Indicates that a brand is associated with or originates from a particular country or nationality.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2f605bc8190a5245aa2ca55cf43 |
completed | March 1, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69a4b2918ea881908698020b995a8eae |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.