Triple
T10023449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayesian networks |
E200666
|
entity |
| Predicate | edgeRepresents |
P88169
|
FINISHED |
| Object | probabilistic dependency |
—
|
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: probabilistic dependency | Statement: [Bayesian networks, edgeRepresents, probabilistic dependency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: edgeRepresents Context triple: [Bayesian networks, edgeRepresents, probabilistic dependency]
-
A.
componentRepresents
Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
-
B.
edgeType
chosen
Indicates the specific kind or category of connection that exists between two related entities.
-
C.
fieldRepresents
Indicates that one field or attribute stands for, encodes, or symbolizes another concept, value, or entity.
-
D.
regionRepresentation
Indicates that one entity serves as a representation, model, or depiction of a specific geographic or spatial region associated with another entity.
-
E.
representsInRelationsWith
Indicates that an entity serves as a representative or proxy for another entity within a specified relationship or set of relationships.
- 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_69ca831c45f08190ac1505cc15076608 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd7c75548190aa604d90d63dc111 |
completed | April 2, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69cd4b7cd4208190b2253583ee2f892c |
completed | April 1, 2026, 4:44 p.m. |
Created at: March 30, 2026, 8:53 p.m.