Triple
T20470971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hermite normal form |
E502190
|
entity |
| Predicate | normalizationDirection |
P114275
|
FINISHED |
| Object | row Hermite normal form |
—
|
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: row Hermite normal form | Statement: [Hermite normal form, normalizationDirection, row Hermite normal form]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: normalizationDirection Context triple: [Hermite normal form, normalizationDirection, row Hermite normal form]
-
A.
normalizationType
Indicates the specific method or scheme used to normalize or standardize data, values, or representations within a given context.
-
B.
normalizationInvolves
Indicates that a normalization process includes or makes use of a particular component, step, or element as part of its execution.
-
C.
refinesNormalization
Indicates that one normalization process or scheme improves, clarifies, or makes more precise another existing normalization.
-
D.
oftenNormalizedTo
chosen
Indicates that one entity is frequently converted, mapped, or standardized into the form or representation of another entity.
-
E.
normalizationAttempt
Indicates an effort to convert something into a standard or consistent form according to defined rules or criteria.
- 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e699608d7c8190910217817e789915 |
completed | April 20, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:33 a.m.