Triple
T17035320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tucker decomposition |
E413306
|
entity |
| Predicate | rankProperty |
P125588
|
FINISHED |
| Object | allows different ranks for different modes |
—
|
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: allows different ranks for different modes | Statement: [Tucker decomposition, rankProperty, allows different ranks for different modes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankProperty Context triple: [Tucker decomposition, rankProperty, allows different ranks for different modes]
-
A.
rankingScope
Indicates the context or domain within which a ranking is defined, interpreted, or applied.
-
B.
rankType
Indicates the specific category or classification of a rank within a ranking or hierarchy system.
-
C.
rankingType
Indicates the specific basis or method by which items are ordered or ranked relative to one another.
-
D.
rankEquivalent
Indicates that two entities hold the same rank or hierarchical level within a given ordering or classification system.
-
E.
rankOverField
Indicates that one entity’s rank or ordering is determined relative to another entity within a specified field or domain.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f05824819091d2aa02e5591e26 |
completed | April 18, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:33 a.m.