Triple
T22964866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Mathematical Olympiad |
E571010
|
entity |
| Predicate | totalNumberOfProblems |
P30117
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [International Mathematical Olympiad, totalNumberOfProblems, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalNumberOfProblems Context triple: [International Mathematical Olympiad, totalNumberOfProblems, 6]
-
A.
numberOfProblems
chosen
Indicates the quantity or count of problems associated with a given entity or situation.
-
B.
numberOfProblemata
Indicates the quantity or count of distinct problems or issues associated with an entity.
-
C.
problemTypeSolved
Indicates that a given problem has been successfully solved or resolved by a particular entity or method.
-
D.
pointsPerProblem
Indicates the number of points assigned to each individual problem within a set of problems.
-
E.
numberOfQuestions
Indicates the total count of questions associated with or contained in a given entity or context.
- 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f763688190aab8f444a1a71577 |
completed | April 29, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:47 p.m.