Triple
T13880197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senators of the College of Justice |
E333691
|
entity |
| Predicate | minimumSize |
P112219
|
FINISHED |
| Object | 24 |
—
|
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: 24 | Statement: [Senators of the College of Justice, minimumSize, 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumSize Context triple: [Senators of the College of Justice, minimumSize, 24]
-
A.
minimumWidth
Indicates that there is a specified smallest allowable or required width for something in the relationship.
-
B.
minimumUnitSize
Indicates that there is a smallest allowable or defined size or quantity for the unit involved in the relationship.
-
C.
recommendedMinimumSize
Indicates the smallest size that is advised or suggested as a minimum for something to be used or considered appropriate.
-
D.
minimumFrameSize
Indicates the smallest allowable or supported size of a frame in the given context or system.
-
E.
hasMinimumSize
Indicates that an entity meets or exceeds a specified minimum size threshold.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a101488190bd790b28033d38b9 |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69de05972f3881909977b4c843984f88 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239524688190a0f2408c239cfcaa |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:15 p.m.