Triple
T19847946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Bann (Northern Ireland Assembly) |
E476920
|
entity |
| Predicate | reducedToFiveMembersFrom |
P45752
|
FINISHED |
| Object | 2017 |
—
|
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: 2017 | Statement: [Upper Bann (Northern Ireland Assembly), reducedToFiveMembersFrom, 2017]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reducedToFiveMembersFrom Context triple: [Upper Bann (Northern Ireland Assembly), reducedToFiveMembersFrom, 2017]
-
A.
reducedNumberOfMPsFrom
Indicates that an entity has experienced a decrease in its number of MPs (members of parliament) originating from the referenced source entity.
-
B.
formerMemberOf
Indicates that an entity once belonged to or was affiliated with a group, organization, or body, but is no longer a member.
-
C.
reducedNumberOf
Indicates that the subject has a smaller quantity or count of the specified object or attribute compared to a prior state or reference level.
-
D.
hadNumberOfMembers
chosen
Indicates that an entity possessed or was associated with a specific count of members at a given time or in a given context.
-
E.
reducedNumberOfVoivodeshipsFrom
Indicates that an entity caused or is associated with a decrease in the number of voivodeships from a specified prior quantity.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6580ba4948190a3260f23d011cc36 |
completed | April 20, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69e537e21d2881909b1be82f02b99d40 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:51 p.m.