Triple
T37814770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yes, Virginia, there is a Santa Claus |
E942742
|
entity |
| Predicate | reprintFrequency |
P1389
|
FINISHED |
| Object | annually at Christmas by many newspapers |
—
|
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: annually at Christmas by many newspapers | Statement: [Yes, Virginia, there is a Santa Claus, reprintFrequency, annually at Christmas by many newspapers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reprintFrequency Context triple: [Yes, Virginia, there is a Santa Claus, reprintFrequency, annually at Christmas by many newspapers]
-
A.
publicationFrequency
chosen
Indicates how often a publication or content is issued, released, or made available over a given period.
-
B.
hasBeenReprintedIn
Indicates that an item (such as a work or edition) has been published again in another source, format, or collection.
-
C.
seriesFrequency
Indicates how often the events or items in a recurring series occur over time.
-
D.
periodicalForm
Indicates that one entity is a periodical publication that serves as the form or medium in which the other entity appears or is expressed.
-
E.
reprintPublisher
Indicates that an entity serves as the publisher responsible for issuing a reprinted edition of a work.
- 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_69f76ee987588190906506e759be5db3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.