Triple
T34792218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donkeyskin |
E1002976
|
entity |
| Predicate | relatedFairyTale |
P106091
|
FINISHED |
| Object | Cinderella |
E1651836
|
NE 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: Cinderella | Statement: [Donkeyskin, relatedFairyTale, Cinderella]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedFairyTale Context triple: [Donkeyskin, relatedFairyTale, Cinderella]
-
A.
associatedTale
Indicates that one entity is linked or connected to a particular tale, story, or narrative.
-
B.
relatedToInFiction
chosen
Indicates that one entity is connected to another within a fictional context, such as a story, universe, or narrative work.
-
C.
originalStories
Indicates that one entity is the creator or source of the original stories associated with another entity.
-
D.
alsoRelatedParable
Indicates that one parable is additionally related to another parable beyond the primary or most obvious connection.
-
E.
hasFolkTaleType
Indicates that an entity (such as a story) is classified as belonging to a particular folk tale type or category.
- F. None of above.
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_69f76db47d408190a24fc7164439ea2d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a376fa3e0e08190be6c829fd8476215 |
completed | June 21, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 3:59 p.m.