Triple
T9186772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Democratic Union Party |
E220478
|
entity |
| Predicate | usesQuotaSystemFor |
P80410
|
FINISHED |
| Object | women's political representation |
—
|
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: women's political representation | Statement: [Democratic Union Party, usesQuotaSystemFor, women's political representation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesQuotaSystemFor Context triple: [Democratic Union Party, usesQuotaSystemFor, women's political representation]
-
A.
oftenUsesQuotaType
chosen
Indicates that an entity frequently employs or relies on a particular type of quota in its typical operations or behavior.
-
B.
supportsProjectQuotas
Indicates that one entity provides or enables project-specific quota limits or enforcement for another entity.
-
C.
usedBySystem
Indicates that something is utilized or operated by a particular system.
-
D.
hasQuotationSystem
Indicates that an entity uses or is associated with a particular system or convention for representing quotations.
-
E.
usedToQuantize
Indicates that one entity serves as the quantization method, scheme, or tool applied to another entity.
- 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_69ca83e6d77c81909862b7afef56b1bf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc31a52508190a83ccd76f3aa039b |
completed | April 1, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69cc66090e5881908889dc1213815626 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:24 p.m.