Triple
T18884114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coatbridge, Chryston and Bellshill (UK Parliament constituency) |
E461912
|
entity |
| Predicate | MPCount |
P41575
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Coatbridge, Chryston and Bellshill (UK Parliament constituency), MPCount, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MPCount Context triple: [Coatbridge, Chryston and Bellshill (UK Parliament constituency), MPCount, 1]
-
A.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
B.
movementCount
Indicates the number of times a movement or relocation action has occurred between the related entities.
-
C.
count
chosen
Indicates the numerical quantity or total number of instances of a specified entity or event.
-
D.
simCount
Indicates the number of times two entities or items are considered similar according to a defined similarity measure.
-
E.
mineCountApproximate
Indicates that the number of mines associated with an entity is estimated or roughly counted rather than known exactly.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3d3dcec8190a468162c6a4482f6 |
completed | April 20, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e27e1481908a8da10b28f07875 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:57 a.m.