Triple
T26944691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magic Mirror |
E678604
|
entity |
| Predicate | asksAndAnswersFormat |
P161355
|
FINISHED |
| Object | call-and-response with the Queen |
—
|
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: call-and-response with the Queen | Statement: [Magic Mirror, asksAndAnswersFormat, call-and-response with the Queen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: asksAndAnswersFormat Context triple: [Magic Mirror, asksAndAnswersFormat, call-and-response with the Queen]
-
A.
canAnswerQuestionsIn
Indicates that an entity has the ability to answer questions within a specified context, domain, or environment.
-
B.
questionForm
Indicates that one entity is expressed or structured in the form of a question directed toward another entity or context.
-
C.
canAnswerQuestions
Indicates that an entity has the ability or capacity to respond correctly or appropriately to questions.
-
D.
questionFormulation
Indicates that one entity formulates, poses, or expresses a question directed toward another entity or context.
-
E.
typicalQuestion
Indicates that an entity is a common or standard question typically asked in a given context or situation.
- 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_69eeeb4d69588190a7c912164a1c37b3 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62083b4288190987cccbed3892ef9 |
completed | May 2, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
| PDg | Predicate description generation | batch_69f6125e54e0819088ee33a20efcc9e6 |
completed | May 2, 2026, 3:03 p.m. |
Created at: April 27, 2026, 6:20 a.m.