Triple
T7337925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moore neighborhood |
E169176
|
entity |
| Predicate | neighborCountFormula |
P29138
|
FINISHED |
| Object | (2r + 1)^2 - 1 (in 2D, excluding 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 - 1 (in 2D, excluding center) | Statement: [Moore neighborhood, neighborCountFormula, (2r + 1)^2 - 1 (in 2D, excluding center)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neighborCountFormula Context triple: [Moore neighborhood, neighborCountFormula, (2r + 1)^2 - 1 (in 2D, excluding center)]
-
A.
neighborhoodSize
chosen
Indicates the size or extent of the surrounding area or local vicinity associated with an entity.
-
B.
innerNeighbor
Indicates that one entity is directly adjacent to another entity on the inside or interior side of a boundary or structure.
-
C.
clusterDensity
Indicates the degree to which elements within a cluster are closely packed or concentrated relative to its size or volume.
-
D.
numberOfDistances
Indicates the count of distinct distance values associated with or measured between entities in a given context.
-
E.
networkLength
Indicates the total measured extent or distance covered by a network (e.g., of connections, links, or paths).
- 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.