Triple
T26853296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Ulstead |
E676114
|
entity |
| Predicate | hostsWeddingOf |
P110874
|
FINISHED |
| Object |
Aurora and Prince Phillip
Aurora and Prince Phillip are the central romantic couple from Disney’s Sleeping Beauty/Maleficent films, uniting the human and fairy realms through their marriage.
|
E1743084
|
NE FINISHED |
How this triple was built (3 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: Aurora and Prince Phillip | Statement: [Kingdom of Ulstead, hostsWeddingOf, Aurora and Prince Phillip]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Aurora and Prince Phillip Triple: [Kingdom of Ulstead, hostsWeddingOf, Aurora and Prince Phillip]
Generated description
Aurora and Prince Phillip are the central romantic couple from Disney’s Sleeping Beauty/Maleficent films, uniting the human and fairy realms through their marriage.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostsWeddingOf Context triple: [Kingdom of Ulstead, hostsWeddingOf, Aurora and Prince Phillip]
-
A.
associatedWithWeddingOf
chosen
Indicates a relationship where something is connected or related to the wedding event of specific individuals.
-
B.
guestAtWedding
Indicates that a person is attending or has attended a particular wedding as a guest.
-
C.
weddingRole
Indicates the specific role or function an entity has in the context of a wedding event.
-
D.
weddingCity
Indicates the city where a wedding takes place or is held.
-
E.
weddingMarchKey
Indicates the musical key in which a wedding march is composed, arranged, or performed.
- F. None of above.
Provenance (6 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_69eee9b9d7708190a15d7485709ae981 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a121351993481908fd6b4a0c03dcf78 |
completed | May 23, 2026, 8:51 p.m. |
| NEDg | Description generation | batch_6a12143774a0819094274f9c58871f16 |
completed | May 23, 2026, 8:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1214e92af48190b857bf935b0fd49d |
completed | May 23, 2026, 8:58 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 5:19 a.m.