Triple
T28520743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Twelve Dancing Princesses |
E721756
|
entity |
| Predicate | hasNumberOfPrincesses |
P189716
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [The Twelve Dancing Princesses, hasNumberOfPrincesses, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfPrincesses Context triple: [The Twelve Dancing Princesses, hasNumberOfPrincesses, 12]
-
A.
princessOf
Indicates that one entity holds the royal title or role of princess in relation to another entity, typically a realm, family, or sovereign.
-
B.
hasNumberOfPalaces
Indicates the specific count of palaces associated with an entity.
-
C.
featuresPrincess
Indicates that something includes or prominently presents a princess as a central element or character.
-
D.
hasNumberOfProngs
Indicates the relationship specifying how many prongs an object or entity possesses.
-
E.
hasCrownCount
Indicates the number of crowns that an entity possesses or is associated with.
- F. None of above. chosen
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_69f01a5cbcc4819083fb4e723378713e |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fbca6c066c8190a1599202f341417f |
completed | May 6, 2026, 11:10 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fbc9d0854c8190aa00093274afebb8 |
completed | May 6, 2026, 11:08 p.m. |
Created at: April 28, 2026, 3:20 a.m.