Triple
T16804029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Putnam Competition |
E408431
|
entity |
| Predicate | problemStyle |
P124701
|
FINISHED |
| Object | proof-based |
—
|
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: proof-based | Statement: [Putnam Competition, problemStyle, proof-based]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: problemStyle Context triple: [Putnam Competition, problemStyle, proof-based]
-
A.
problemType
Indicates the specific category or classification of a problem within a defined problem space or system.
-
B.
problemStatement
Indicates that an entity presents, defines, or expresses a specific problem or issue to be addressed.
-
C.
correctedProblem
Indicates that one entity has fixed or amended an error or issue present in another entity.
-
D.
problems
Indicates that one entity has issues, difficulties, or complications associated with or caused by another entity.
-
E.
typicalProblem
Indicates that a situation, issue, or obstacle is representative or characteristic of the usual problems encountered in a given context.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2ca46f88190b56e81d75012496c |
completed | April 18, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69e319d0fdb8819088425bd82431640f |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326bac94481908c082117553320f8 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:22 a.m.