Triple
T1248988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pascal's triangle |
E26830
|
entity |
| Predicate | rowSumProperty |
P19439
|
FINISHED |
| Object | sum of entries in nth row equals 2^n |
—
|
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: sum of entries in nth row equals 2^n | Statement: [Pascal's triangle, rowSumProperty, sum of entries in nth row equals 2^n]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rowSumProperty Context triple: [Pascal's triangle, rowSumProperty, sum of entries in nth row equals 2^n]
-
A.
cumulativeProperty
chosen
Indicates that a property of a whole is derived by aggregating or summing corresponding properties of its parts or components.
-
B.
numberOfColumns
Indicates the total count of vertical divisions (columns) associated with or contained in a given structure or dataset.
-
C.
rows
Indicates that one entity is arranged in a horizontal line or sequence relative to another, typically as part of a grid or tabular structure.
-
D.
hasTotalNumber
Indicates that an entity is associated with a specific overall count or sum of items, elements, or units.
-
E.
numberOfPropertiesManaged
Indicates the total count of properties that an entity is responsible for managing.
- 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_69a49487a9c48190ba9b05348fd1b53f |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf83b32c81908648e5748b897247 |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6b075881908e867c25b5080e25 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.