Triple
T2463453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XLII |
E54586
|
entity |
| Predicate | numericDecomposition |
P39997
|
FINISHED |
| Object | 50 - 10 + 1 + 1 |
—
|
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: 50 - 10 + 1 + 1 | Statement: [XLII, numericDecomposition, 50 - 10 + 1 + 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numericDecomposition Context triple: [XLII, numericDecomposition, 50 - 10 + 1 + 1]
-
A.
decimalized
Indicates that something has been converted into or expressed in decimal form, typically changing from another numeral or measurement system to a base-10 representation.
-
B.
number
Indicates that one entity is associated with a specific numerical value or count in relation to another entity or context.
-
C.
parallelDivision
Indicates that one entity is divided or partitioned in a way that runs parallel to the division or partitioning of another entity.
-
D.
primeFactorization
Indicates that one entity is the decomposition of another entity into a multiset or sequence of prime factors whose product equals the original.
-
E.
generalizedForm
Indicates that one entity is a more abstract, generalized version or broader form of another entity.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0b3ea308190a6d8499c2a542c50 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd2baee308190bdaa41ef1f6bc9cc |
completed | March 7, 2026, 7:24 a.m. |
Created at: March 6, 2026, 9:44 p.m.