Triple
T10334260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinckney Plan |
E242958
|
entity |
| Predicate | proposedChamber |
P61483
|
FINISHED |
| Object | bicameral legislature |
—
|
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: bicameral legislature | Statement: [Pinckney Plan, proposedChamber, bicameral legislature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proposedChamber Context triple: [Pinckney Plan, proposedChamber, bicameral legislature]
-
A.
forChamber
chosen
Indicates that something is intended for use in, associated with, or belonging to a particular chamber.
-
B.
chamberOf
Indicates that one entity is a chamber, room, or enclosed space that is part of, contained within, or assigned to another entity.
-
C.
chamber2
Indicates that one entity serves as a secondary or inner chamber, room, or compartment associated with another entity.
-
D.
chamberedFor
Indicates that a firearm is designed or configured to safely accept and fire a specific cartridge or ammunition type in its chamber.
-
E.
previousChamber
Indicates that one legislative or deliberative chamber directly precedes another in an ordered sequence or process.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e91fdb2081909866c6ecf417d75a |
completed | April 7, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69d4df9dc3208190bf1bd106f44f6202 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 11:53 a.m.