Triple
T7337936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moore neighborhood |
E169176
|
entity |
| Predicate | relationToVonNeumann |
P77123
|
FINISHED |
| Object | superset of von Neumann neighborhood in 2D |
—
|
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: superset of von Neumann neighborhood in 2D | Statement: [Moore neighborhood, relationToVonNeumann, superset of von Neumann neighborhood in 2D]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToVonNeumann Context triple: [Moore neighborhood, relationToVonNeumann, superset of von Neumann neighborhood in 2D]
-
A.
valueRelation
Indicates a comparative or associative relationship between the values or magnitudes of two or more entities.
-
B.
zetaRelation
Indicates a specialized, context-dependent association between entities whose exact nature is defined by the specific system or theory using the term "zetaRelation".
-
C.
relatedTheorem
Indicates that one theorem is connected to another through a logical, thematic, or derivational relationship.
-
D.
continuityRelation
Indicates a relationship where one entity directly follows, extends, or maintains an unbroken connection with another in space, time, or logical sequence.
-
E.
successionRelation
Indicates that one entity follows another in an ordered sequence, such as in time, position, or rank.
- 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_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. |
| PDg | Predicate description generation | batch_69c6f3463d0481908aed9ed43a8ac6a8 |
completed | March 27, 2026, 9:14 p.m. |
Created at: March 27, 2026, 3:04 p.m.