Triple
T1260345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 19th Judicial Circuit of Virginia |
E12483
|
entity |
| Predicate | numberOfCircuitsInSystem |
P26350
|
FINISHED |
| Object | 31 |
—
|
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: 31 | Statement: [19th Judicial Circuit of Virginia, numberOfCircuitsInSystem, 31]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCircuitsInSystem Context triple: [19th Judicial Circuit of Virginia, numberOfCircuitsInSystem, 31]
-
A.
hasCircuit
Indicates that an entity is equipped with, contains, or is associated with an electrical or logical circuit.
-
B.
circuitType
Indicates the specific kind or category of electrical circuit associated with an entity.
-
C.
numberOfTerminals
Indicates the total count of terminal points or endpoints associated with an entity.
-
D.
circuit
Indicates that one entity forms or participates in an electrical or logical pathway that allows current or signals to flow through a connected system involving another entity.
-
E.
pinCount
Indicates the number of pins associated with or assigned to a given entity.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc503e88190b237210a61228dd8 |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6eefbc81908dddd7d2ef368186 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd98b62c8190a5f6710345c0537d |
completed | March 1, 2026, 10:28 p.m. |
Created at: March 1, 2026, 7:50 p.m.