Triple
T1382111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaussian elimination |
E29360
|
entity |
| Predicate | canDetect |
P15551
|
FINISHED |
| Object | linear dependence of rows |
—
|
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: linear dependence of rows | Statement: [Gaussian elimination, canDetect, linear dependence of rows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canDetect Context triple: [Gaussian elimination, canDetect, linear dependence of rows]
-
A.
canRecognize
chosen
Indicates that one entity has the ability to identify or distinguish another entity based on its features or characteristics.
-
B.
requiresDetectionOf
Indicates that one entity can only occur, be valid, or proceed if another entity has first been detected or identified.
-
C.
canBe
Indicates that one entity has the potential, permission, or capability to become, perform as, or be classified as another entity.
-
D.
canUse
Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
-
E.
detectorType
Indicates the specific kind or category of detector associated with an entity or measurement.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c3361bf08190b3f6bbf82e17685b |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befe343c81909f758440a531b5be |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.