Triple
T6833237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Successive Over-Relaxation |
E157387
|
entity |
| Predicate | specialCaseWhen |
P7025
|
FINISHED |
| Object | ω = 1 gives Gauss–Seidel method |
—
|
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: ω = 1 gives Gauss–Seidel method | Statement: [Successive Over-Relaxation, specialCaseWhen, ω = 1 gives Gauss–Seidel method]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specialCaseWhen Context triple: [Successive Over-Relaxation, specialCaseWhen, ω = 1 gives Gauss–Seidel method]
-
A.
specialCaseOf
chosen
Indicates that one entity represents a more specific, exceptional, or restricted instance of the general situation, rule, or relationship expressed by another entity.
-
B.
specialValue
Indicates that an entity possesses a distinguished or exceptional value compared to typical or default values in the given context.
-
C.
specialAppearance
Indicates that an entity makes a notable or exceptional appearance distinct from its usual or regular presence.
-
D.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
E.
usedInCase
Indicates that something (such as an item, method, or piece of information) is employed or applied within a particular case or instance.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d62b1e8c8190a81d91191a54b073 |
completed | March 27, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69c6d09d95f0819091ca7f897dc21efe |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:18 p.m.