Triple
T22450216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BBA 1997 |
E554969
|
entity |
| Predicate | mainMechanism |
P8166
|
FINISHED |
| Object | spending cuts |
—
|
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: spending cuts | Statement: [BBA 1997, mainMechanism, spending cuts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainMechanism Context triple: [BBA 1997, mainMechanism, spending cuts]
-
A.
mechanismExample
Indicates that one entity serves as an illustrative example of the mechanism or process by which another entity operates or produces an effect.
-
B.
hasMechanism
chosen
Indicates that one entity operates, functions, or produces an effect through the specified mechanism or process.
-
C.
mechanicalFunction
Indicates that one entity serves as the mechanical role, operation, or function performed by another entity or system.
-
D.
interactionMechanism
Indicates the process or means by which one entity affects, influences, or interacts with another.
-
E.
mentionsMechanism
Indicates that one entity explicitly refers to or describes the mechanism, process, or causal pathway by which another entity operates or produces an effect.
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4ae8a08190ba6027f036ce62af |
completed | April 29, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69e898ad961c819098fd1e46129bddcc |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:48 p.m.