Triple
T22423672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | P. Berlin 3033 |
E554310
|
entity |
| Predicate | containsTaleType |
P116843
|
FINISHED |
| Object | court tales |
—
|
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: court tales | Statement: [P. Berlin 3033, containsTaleType, court tales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsTaleType Context triple: [P. Berlin 3033, containsTaleType, court tales]
-
A.
hasFolkTaleType
chosen
Indicates that an entity (such as a story) is classified as belonging to a particular folk tale type or category.
-
B.
hasStandaloneTales
Indicates that an entity includes or is associated with independent, self-contained stories that can be understood without relying on a larger narrative.
-
C.
hasStorylineType
Indicates that an entity’s storyline belongs to or is categorized under a specific type or narrative classification.
-
D.
hasStaffTypeInStory
Indicates that a story involves or is associated with a particular type or category of staff.
-
E.
hasVariantStoriesIn
Indicates that an entity has alternative or differing narrative versions that occur or are found within a specified context or source.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a2af620819083338127e78137dc |
completed | April 29, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:47 p.m.