Triple
T1523290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clay Mathematics Institute |
E32277
|
entity |
| Predicate | numberOfMillenniumProblems |
P30115
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Clay Mathematics Institute, numberOfMillenniumProblems, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMillenniumProblems Context triple: [Clay Mathematics Institute, numberOfMillenniumProblems, 7]
-
A.
numberOfMysteries
Indicates the quantity or count of mysteries associated with a given entity.
-
B.
numberOfVisionaries
Indicates the quantity or count of entities classified as visionaries in a given context.
-
C.
numberOfNewMysteries
Indicates the count of newly introduced or discovered mysteries associated with an entity or context.
-
D.
commonlySolvedBy
Indicates that a problem, task, or issue is typically addressed or resolved through a particular method, tool, or agent.
-
E.
mathematicallyFormulatedBy
Indicates that something (such as a concept, model, or theory) is expressed or defined using mathematical formulations created by a particular agent.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93d4756888190bf3872154de11539 |
completed | March 5, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69a907ac7ea081908dd95bb5cc3b9847 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a93d462f208190b27ef5cd631bce12 |
completed | March 5, 2026, 8:22 a.m. |
Created at: March 4, 2026, 7:26 p.m.