Triple
T1369544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The New York Times Magazine |
E30080
|
entity |
| Predicate | typicalPublicationDay |
P27008
|
FINISHED |
| Object | Sunday |
—
|
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: Sunday | Statement: [The New York Times Magazine, typicalPublicationDay, Sunday]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPublicationDay Context triple: [The New York Times Magazine, typicalPublicationDay, Sunday]
-
A.
typicalDates
Indicates the usual or standard dates during which something typically occurs, is valid, or is scheduled.
-
B.
publishedFor
Indicates that something (such as a work, document, or content) is published with a particular audience, recipient, or target group in mind.
-
C.
typicalAwardDate
Indicates the date on which an award is customarily or normally given or conferred.
-
D.
publicationMonth
Indicates the calendar month in which a publication was released or made publicly available.
-
E.
typicalMonthOfOccurrence
Indicates the month in which something most commonly or typically occurs.
- 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2d60fdc8190a9954b74ca2b2541 |
completed | March 1, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69a4befb08b88190be966fa1aadd4bcd |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bfc2134c81909cbaaa151d96e9a8 |
completed | March 1, 2026, 10:37 p.m. |
Created at: March 1, 2026, 7:57 p.m.