Triple
T1069756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pulitzer Prize for International Reporting |
E23297
|
entity |
| Predicate | typicalSubjects |
P450
|
FINISHED |
| Object | foreign correspondence |
—
|
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: foreign correspondence | Statement: [Pulitzer Prize for International Reporting, typicalSubjects, foreign correspondence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSubjects Context triple: [Pulitzer Prize for International Reporting, typicalSubjects, foreign correspondence]
-
A.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
typicalAudience
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
D.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
E.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
- 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_69a493ee1f908190992b5f0d1b04459b |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b914b4908190886d6698294c6b5b |
completed | March 1, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69a4b73844708190a16c9e9824ca2fb6 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.