Triple
T25793443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NKo |
E649608
|
entity |
| Predicate | supportsBidirectionalAlgorithm |
P56342
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [NKo, supportsBidirectionalAlgorithm, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsBidirectionalAlgorithm Context triple: [NKo, supportsBidirectionalAlgorithm, yes]
-
A.
hasBidirectionalClass
Indicates that there is a mutual, two-way class relationship between the involved entities, where each class is related to the other.
-
B.
supportsOptimizationAlgorithm
chosen
Indicates that one entity is capable of running, integrating, or being compatible with a specified optimization algorithm.
-
C.
supportsBidirectionalPower
Indicates that an entity can both supply and receive power, allowing electrical energy to flow in either direction between connected systems.
-
D.
hasTwoOperationalDirections
Indicates that an entity supports or functions in two distinct operational directions or modes.
-
E.
supportsSymmetricVariant
Indicates that one entity is compatible with or enables the use of a symmetric (mirrored or bidirectional) variant of another entity or feature.
- 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_69e7ab33e9308190afe415dc6f9e8876 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
Created at: April 22, 2026, 6:01 a.m.