Triple
T2406672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reform Act 1867 |
E50290
|
entity |
| Predicate | transferredSeatsTo |
P39233
|
FINISHED |
| Object | larger towns and counties |
—
|
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: larger towns and counties | Statement: [Reform Act 1867, transferredSeatsTo, larger towns and counties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transferredSeatsTo Context triple: [Reform Act 1867, transferredSeatsTo, larger towns and counties]
-
A.
UNSeatTransferDate
Indicates the date on which a seat is transferred from one holder to another.
-
B.
transportedOver
Indicates that something is moved or carried across or along a specified medium, route, or surface.
-
C.
hasReservedSeats
Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
-
D.
originalSeat
Indicates the seat that was initially assigned or occupied before any changes, moves, or reassignments occurred.
-
E.
relocatedBetween
Indicates that an entity changed location from one place to another during a specified time interval or between two reference points.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abceab9ce881909ae0a2f34515c11e |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5a530e8819094105aa92dfaf6b3 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abceaa42b88190a790355100fede3d |
completed | March 7, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:58 p.m.