Triple
T21440078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna (Surfacing) |
E528914
|
entity |
| Predicate | characterInBookByAuthorNationality |
P76869
|
FINISHED |
| Object | Canadian |
—
|
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: Canadian | Statement: [Anna (Surfacing), characterInBookByAuthorNationality, Canadian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInBookByAuthorNationality Context triple: [Anna (Surfacing), characterInBookByAuthorNationality, Canadian]
-
A.
authorNationality
Indicates the relationship between an author and the country or nationality with which that author is identified.
-
B.
appearsInWorkByAuthorNationality
chosen
Indicates that an entity appears in a work created by an author of a specified nationality.
-
C.
characterInBookBy
Indicates that a character appears in a book that was written by a specified author.
-
D.
associatedWithCountryInFiction
Indicates a fictional relationship in which an entity is linked or connected to a particular country within a fictional context or narrative.
-
E.
coAuthorNationality
Indicates that two or more co-authors of a work share the same nationality or have nationalities being related in the context of their co-authorship.
- 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b700237c8190bbcb4bedc4242719 |
completed | April 22, 2026, 11:54 a.m. |
| PD | Predicate disambiguation | batch_69e61639ee288190889ffd500d1260f6 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 16, 2026, 6:05 p.m.