Triple
T14306370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Uqlidisi |
E354705
|
entity |
| Predicate | mathematicalConcept |
P43795
|
FINISHED |
| Object | decimal notation |
—
|
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: decimal notation | Statement: [Al-Uqlidisi, mathematicalConcept, decimal notation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mathematicalConcept Context triple: [Al-Uqlidisi, mathematicalConcept, decimal notation]
-
A.
mathematicalObject
chosen
Indicates that the subject is a mathematical entity or construct, such as a number, function, set, or structure, within a mathematical context.
-
B.
hasMathematicalProperty
Indicates that one entity possesses or exhibits a specific mathematical property or characteristic.
-
C.
mathematicallyExpressedBy
Indicates that something (such as a concept, quantity, or relationship) is represented or captured using a specific mathematical expression or formulation.
-
D.
mathematicalLevel
Indicates the degree or complexity of mathematical knowledge, skill, or sophistication associated with an entity.
-
E.
scientificConcept
Indicates that one entity is a scientific idea, principle, or theory that defines, explains, or characterizes the other entity.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b156b0819083f2bd319deed1b6 |
completed | April 14, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a8f81f08190af737e1654847aa6 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:12 a.m.