Triple
T7678435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yang–Mills existence and mass gap problem |
E173924
|
entity |
| Predicate | hasNoKnown |
P52085
|
FINISHED |
| Object | complete rigorous solution |
—
|
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: complete rigorous solution | Statement: [Yang–Mills existence and mass gap problem, hasNoKnown, complete rigorous solution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoKnown Context triple: [Yang–Mills existence and mass gap problem, hasNoKnown, complete rigorous solution]
-
A.
hasUnknown
Indicates that an entity possesses or is associated with information, attributes, or values that are not known or not specified.
-
B.
hadNo
Indicates that one entity completely lacked or did not possess another entity, attribute, or relationship.
-
C.
hasNoEvidenceOf
chosen
Indicates that there is no supporting proof, data, or documentation confirming the existence or occurrence of the referenced condition, event, or relationship.
-
D.
hasUnknownGivenName
Indicates that the given (first) name of the entity is not known or not specified.
-
E.
ignorantOf
Indicates that one entity lacks knowledge or awareness of another entity or of some specific fact, topic, or situation.
- 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_69c6995703e0819081de77361b602e78 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7048b0b448190889bd40e0a38e51a |
completed | March 27, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69c701618d3481908be84b76f36ac5a1 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 4:01 p.m.