Triple
T1177484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pulitzer Prize for Breaking News Photography |
E25060
|
entity |
| Predicate | hasAwardedForExamples |
P26270
|
FINISHED |
| Object | natural disasters coverage |
—
|
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: natural disasters coverage | Statement: [Pulitzer Prize for Breaking News Photography, hasAwardedForExamples, natural disasters coverage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAwardedForExamples Context triple: [Pulitzer Prize for Breaking News Photography, hasAwardedForExamples, natural disasters coverage]
-
A.
hasAwarded
Indicates that one entity has given or conferred an award to another entity.
-
B.
hasAwardedDiscipline
Indicates that one entity has formally imposed or granted a disciplinary action or sanction upon another entity.
-
C.
hasAwardedFormat
Indicates that one entity has granted or assigned a particular award format or type to another entity.
-
D.
hasAwardedMedium
Indicates that one entity has granted or conferred a specific medium-level award or recognition to another entity.
-
E.
hasAwardedWorkType
Indicates that an entity has granted or is associated with a specific type or category of work that has received an award.
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd53e4b48190abb2167f8074a6bc |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5844348190b01ac6506906ba3b |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd52177081908c5cec8e731b836e |
completed | March 1, 2026, 10:27 p.m. |
Created at: March 1, 2026, 7:45 p.m.