Triple
T5132409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irish House of Lords |
E115731
|
entity |
| Predicate | hadChamberType |
P4152
|
FINISHED |
| Object | bicameral legislature upper house |
—
|
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 upper house | Statement: [Irish House of Lords, hadChamberType, bicameral legislature upper house]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadChamberType Context triple: [Irish House of Lords, hadChamberType, bicameral legislature upper house]
-
A.
hasChamber
Indicates that one entity possesses, contains, or is associated with a distinct enclosed space or compartment (a chamber).
-
B.
hasChamberStructure
Indicates that an entity possesses a specific internal chamber or compartmentalized structural organization.
-
C.
chamberType
chosen
Indicates the specific kind or category of chamber associated with an entity (e.g., room, compartment, or enclosed space type).
-
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.
hasChamberNumber
Indicates that an entity is associated with a specific chamber identified by a particular number.
- 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_69bd444426bc819099ccd23f141e22aa |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7fef2e8c8190982dd67f50295ada |
completed | March 20, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69bd77ac2fc48190abeebb003a82384c |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:42 p.m.