Triple
T13987932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subjacency |
E336489
|
entity |
| Predicate | typicalBoundingNode |
P84052
|
FINISHED |
| Object | IP |
—
|
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: IP | Statement: [Subjacency, typicalBoundingNode, IP]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBoundingNode Context triple: [Subjacency, typicalBoundingNode, IP]
-
A.
typicalBoundary
chosen
Indicates that one entity serves as the usual or characteristic boundary or limit for another entity.
-
B.
isBoundaryFor
Indicates that one entity serves as the limiting edge, border, or enclosing extent that defines the spatial or conceptual bounds of another entity.
-
C.
dimensionBoundType
Indicates the type or nature of the constraint that bounds a given dimension in a relationship.
-
D.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
E.
typicalTopology
Indicates the usual or most common network or structural arrangement that characterizes how the related entities are organized or interconnected.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ea537408190bb9d35963886803f |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.