Triple
T10867997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parliamentary Constituencies Act 2020 |
E256573
|
entity |
| Predicate | fixesNumberOf |
P87695
|
FINISHED |
| Object | Members of Parliament in the House of Commons |
—
|
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: Members of Parliament in the House of Commons | Statement: [Parliamentary Constituencies Act 2020, fixesNumberOf, Members of Parliament in the House of Commons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fixesNumberOf Context triple: [Parliamentary Constituencies Act 2020, fixesNumberOf, Members of Parliament in the House of Commons]
-
A.
setsNumberOf
chosen
Indicates that one entity assigns or defines the numerical quantity or count associated with another entity.
-
B.
hasFixedCount
Indicates that something is associated with a specific, unchanging number or quantity.
-
C.
numberOfRivets
Indicates the quantitative relationship specifying how many rivets are associated with a given object or structure.
-
D.
sampleNumber
Indicates that an entity is identified or associated with a specific sample number within a set of samples.
-
E.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7516f9b08819096b9438878bf36c9 |
completed | April 9, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d70d308dfc81908792f98cfb871392 |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.