Triple
T30983988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landsbanki |
E789467
|
entity |
| Predicate | effectOnHouseOfFraser |
P181444
|
FINISHED |
| Object | constrained alternative ownership and financing options |
—
|
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: constrained alternative ownership and financing options | Statement: [Landsbanki, effectOnHouseOfFraser, constrained alternative ownership and financing options]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnHouseOfFraser Context triple: [Landsbanki, effectOnHouseOfFraser, constrained alternative ownership and financing options]
-
A.
impactOnScotland
Indicates the effect or consequences that something has specifically on Scotland.
-
B.
effectOnEngland
Indicates the impact or influence that something has on England.
-
C.
effectOnHabsburgs
Indicates the impact or consequences that something has on the Habsburgs as a group or dynasty.
-
D.
effectOnHouseElves
Indicates the impact or consequences that an action, event, or condition has on house elves.
-
E.
effectOnFrance
Indicates the impact, influence, or consequences that something has on France.
- 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_69f224c550b081909ddfceb0c3d03bdd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7764ab1fc81909f9348db87bd7692 |
completed | May 3, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f76905d9c88190b1ee810bc9ab644f |
completed | May 3, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69f77648979c8190b6cdbb835ab8987c |
completed | May 3, 2026, 4:22 p.m. |
Created at: April 29, 2026, 8:55 p.m.