Triple
T24612452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selby and Ainsty |
E609155
|
entity |
| Predicate | wasPreviouslySafeSeatFor |
P75353
|
FINISHED |
| Object | Conservative Party (UK) |
—
|
NE NERFINISHED |
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: Conservative Party (UK) | Statement: [Selby and Ainsty, wasPreviouslySafeSeatFor, Conservative Party (UK)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasPreviouslySafeSeatFor Context triple: [Selby and Ainsty, wasPreviouslySafeSeatFor, Conservative Party (UK)]
-
A.
hasBeenSafeSeatFor
chosen
Indicates that a political position or constituency has consistently been held securely by a particular party or candidate, with little risk of losing it in elections.
-
B.
isSafeSeatFor
Indicates that one entity is a suitable and secure seating option for another entity, posing no unacceptable risk or harm.
-
C.
seatIs
Indicates that one entity functions as the seat or seating position of another entity.
-
D.
seatSince
Indicates that an entity has held a particular seat, position, or place continuously since a specified point in time.
-
E.
hasPredecessorSeat
Indicates that one seat directly precedes another seat in an ordered sequence or arrangement.
- 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_69e2c4d1140081909c58667bf68f80c3 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:31 a.m.