Triple
T7337926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moore neighborhood |
E169176
|
entity |
| Predicate | centerIncludedCountFormula |
P41948
|
FINISHED |
| Object | (2r + 1)^2 (in 2D, including center) |
—
|
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: (2r + 1)^2 (in 2D, including center) | Statement: [Moore neighborhood, centerIncludedCountFormula, (2r + 1)^2 (in 2D, including center)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: centerIncludedCountFormula Context triple: [Moore neighborhood, centerIncludedCountFormula, (2r + 1)^2 (in 2D, including center)]
-
A.
areCountedBy
Indicates that one entity serves as the counting mechanism, record, or process by which the quantity of another entity is determined.
-
B.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
C.
positionIncluded
Indicates that one position or spatial region is entirely contained within another position or spatial region.
-
D.
countingRule
chosen
Indicates the rule or method used to count or quantify items, events, or entities in a given context.
-
E.
count
Indicates the numerical quantity or total number of instances of a specified entity or event.
- 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_69c68a57710481909f0c1f3c6ebdb6f2 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:04 p.m.