Triple
T22118454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Non-constituency Member of Parliament |
E546599
|
entity |
| Predicate | maximumNumberOfNCMPs |
P147057
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Non-constituency Member of Parliament, maximumNumberOfNCMPs, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumNumberOfNCMPs Context triple: [Non-constituency Member of Parliament, maximumNumberOfNCMPs, 9]
-
A.
maximumNumberOfSegments
Indicates the greatest allowable or observed count of discrete segments into which something can be or is divided.
-
B.
maximumClusterCount
Indicates the highest number of clusters that are allowed or can be formed in a given context.
-
C.
maxSMPConfiguration
Indicates the configuration in which a system or component is set to use the maximum supported symmetric multiprocessing (SMP) resources or capabilities.
-
D.
maxNumberOfProcessors
Indicates the maximum number of processors that are allowed or supported in a given context or configuration.
-
E.
maximumTermCount
Indicates the highest number of terms that are allowed or considered within a given context or operation.
- F. None of above. chosen
Provenance (4 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1294fcf2c81909b610e03a0f1921f |
completed | April 28, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e7222d208c819098b12c13e31af629 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:31 p.m.