Triple
T26253239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | von Neumann neighborhood |
E656652
|
entity |
| Predicate | hasAdjacencyType |
P168053
|
FINISHED |
| Object | orthogonal adjacency |
—
|
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: orthogonal adjacency | Statement: [von Neumann neighborhood, hasAdjacencyType, orthogonal adjacency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdjacencyType Context triple: [von Neumann neighborhood, hasAdjacencyType, orthogonal adjacency]
-
A.
hasJunctionType
Indicates the specific kind or classification of a junction associated with an entity.
-
B.
hasAdjacentRole
Indicates that one role is positioned directly next to or alongside another role within a defined structure or sequence.
-
C.
hasArcType
Indicates that one entity is associated with, or characterized by, a specific type or category of arc.
-
D.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
E.
hasAdjacentUse
Indicates that one entity is used or occurs directly next to another in space, time, or sequence.
- 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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f673633d288190b52ceb9f8a057c44 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 26, 2026, 9:07 p.m.