Triple
T36151646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | red-black tree |
E1045599
|
entity |
| Predicate | nodeDegree |
P120531
|
FINISHED |
| Object | at most 2 children per node |
—
|
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: at most 2 children per node | Statement: [red-black tree, nodeDegree, at most 2 children per node]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nodeDegree Context triple: [red-black tree, nodeDegree, at most 2 children per node]
-
A.
vertexDegree
chosen
Indicates the number of edges incident to a given vertex in a graph.
-
B.
degreeMap
Indicates a mapping that associates each entity with its corresponding degree or level within a specified structure or context.
-
C.
numberOfCoreDegrees
Indicates the quantitative count of core academic degrees associated with an entity.
-
D.
isDegreeOf
Indicates that one entity is an academic or professional degree held, pursued, or associated with another entity.
-
E.
networkDepth
Indicates the hierarchical level or number of intermediary layers between connected elements within a network structure.
- 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_69f76e37ace88190a906b107d388f5d1 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.