Triple
T27868946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | white chamber of the Tricameral Parliament |
E704437
|
entity |
| Predicate | numberOfChambersInSystem |
P1545
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [white chamber of the Tricameral Parliament, numberOfChambersInSystem, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfChambersInSystem Context triple: [white chamber of the Tricameral Parliament, numberOfChambersInSystem, 3]
-
A.
numberOfChambers
chosen
Indicates the count of distinct chambers or compartments associated with an entity.
-
B.
chamberSystem
Indicates a relationship where an entity functions as, belongs to, or is part of a particular chamber system (e.g., a structural, mechanical, or organizational chamber arrangement).
-
C.
hasChambersFor
Indicates that one entity contains or provides designated chambers or compartments intended for use by another entity.
-
D.
hasDuplicateChambers
Indicates that an entity possesses two or more chambers that are identical or functionally equivalent.
-
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_69ef840f12408190b539d00d79658abf |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69ff246e0d4481908bcec718e1d4025b |
completed | May 9, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69ff23cb70ac81909b776ace4597ae9c |
completed | May 9, 2026, 12:08 p.m. |
Created at: April 27, 2026, 6:23 p.m.