Triple
T14726538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheltenham (UK Parliament constituency) |
E345958
|
entity |
| Predicate | numberOfMPsBefore |
P82981
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Cheltenham (UK Parliament constituency), numberOfMPsBefore, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMPsBefore Context triple: [Cheltenham (UK Parliament constituency), numberOfMPsBefore, 2]
-
A.
hasNumberOfMPs
chosen
Indicates the relationship that specifies how many members of parliament (MPs) are associated with a given entity.
-
B.
hasNumberOfMSPs
Indicates the relationship specifying how many managed service providers (MSPs) are associated with or involved in a given entity or context.
-
C.
numberOfParliaments
Indicates the count of distinct parliaments associated with or relevant to a given entity.
-
D.
previousNumberOfConstituents
Indicates the number of constituents an entity had at an earlier point in time, before its current state.
-
E.
numberOfMembersUpperHouse
Indicates the total count of individuals serving as members in the upper house of a legislative body.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec26013c8819090512f8b4df9cc87 |
completed | April 14, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69de657e174481909da0437556334a04 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:29 a.m.