Triple
T15187152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Edward, Prince of Wales (The King’s Speech) |
E362906
|
entity |
| Predicate | impactOnBertie |
P55427
|
FINISHED |
| Object | forces Bertie to become king |
—
|
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: forces Bertie to become king | Statement: [Prince Edward, Prince of Wales (The King’s Speech), impactOnBertie, forces Bertie to become king]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnBertie Context triple: [Prince Edward, Prince of Wales (The King’s Speech), impactOnBertie, forces Bertie to become king]
-
A.
impactOnMonarch
chosen
Indicates a relationship where an action, event, or condition produces an effect or consequence on a monarch.
-
B.
impactOnScotland
Indicates the effect or consequences that something has specifically on Scotland.
-
C.
impactOnSubject
Indicates the effect, influence, or consequence that one entity, event, or action has on a specified subject.
-
D.
impactOnLeader
Indicates that one entity has an effect, influence, or consequence on a leader within a given context.
-
E.
impactDescription
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0067995fc8190b048f15086bd42f0 |
completed | April 15, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:09 a.m.