Triple
T383567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reform Act 1832 |
E8730
|
entity |
| Predicate | reducedRepresentationOf |
P10727
|
FINISHED |
| Object | rotten boroughs |
—
|
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: rotten boroughs | Statement: [Reform Act 1832, reducedRepresentationOf, rotten boroughs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reducedRepresentationOf Context triple: [Reform Act 1832, reducedRepresentationOf, rotten boroughs]
-
A.
reducesTo
Indicates that one expression, structure, or state can be transformed or simplified into another, typically more basic or canonical, form.
-
B.
reduces
Indicates that one entity causes a decrease in the amount, intensity, degree, or impact of another entity.
-
C.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
D.
reducedCostOf
Indicates that one entity represents a lowered or discounted cost associated with another entity, typically compared to a standard or original price.
-
E.
canRepresent
Indicates that one entity is capable of serving as a valid stand-in, proxy, or expression for another entity in a given context.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec40ff8c81909306eb2dfe1512af |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96602188190b0cbc167f55a9237 |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea2dc3088190a2aeb4496aff3582 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.