Triple
T6833385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaussian rationals ℚ(i) |
E157390
|
entity |
| Predicate | fractionFieldOf |
P27199
|
FINISHED |
| Object | Gaussian integers ℤ[i] |
—
|
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: Gaussian integers ℤ[i] | Statement: [Gaussian rationals ℚ(i), fractionFieldOf, Gaussian integers ℤ[i]]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fractionFieldOf Context triple: [Gaussian rationals ℚ(i), fractionFieldOf, Gaussian integers ℤ[i]]
-
A.
hasFraction
Indicates that one entity represents a fractional part or proportion of another entity.
-
B.
fieldOfFractions
chosen
Indicates that one mathematical structure is the field formed by taking all possible fractions of elements from a given integral domain.
-
C.
unitFractionalName
Indicates that one entity is the name or label used to represent a fractional unit of another entity (such as a measurement or quantity).
-
D.
destroysFractionOf
Indicates that one entity damages or eliminates a specified fraction or proportion of another entity.
-
E.
fractionAppointed
Indicates the proportion of positions or roles within a group or organization that have been formally filled or assigned.
- 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.