Triple
T5828390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Tale of Mrs. Tiggy-Winkle |
E129284
|
entity |
| Predicate | isPartOfCanon |
P977
|
FINISHED |
| Object | Beatrix Potter canon |
—
|
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: Beatrix Potter canon | Statement: [The Tale of Mrs. Tiggy-Winkle, isPartOfCanon, Beatrix Potter canon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartOfCanon Context triple: [The Tale of Mrs. Tiggy-Winkle, isPartOfCanon, Beatrix Potter canon]
-
A.
hasPlaceInCanon
Indicates that something holds a specific status or position within an established canon or authoritative body of works.
-
B.
notInCanonOf
Indicates that something is excluded from, or does not belong to, the officially recognized canon of a given work or universe.
-
C.
followsInCanon
Indicates that one entity occurs later than and in continuity with another within an established narrative or canonical sequence.
-
D.
eraInCanon
Indicates that a subject belongs to, occurs within, or is classified as part of a specific era defined in a canon or fictional continuity.
-
E.
inCanonOf
chosen
Indicates that one entity is officially recognized as part of the established canon or authoritative body of works 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:53 p.m.