Triple
T30983983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landsbanki |
E789467
|
entity |
| Predicate | relationshipToBaugur |
P207331
|
FINISHED |
| Object | principal bank creditor following Baugur insolvency |
—
|
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: principal bank creditor following Baugur insolvency | Statement: [Landsbanki, relationshipToBaugur, principal bank creditor following Baugur insolvency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToBaugur Context triple: [Landsbanki, relationshipToBaugur, principal bank creditor following Baugur insolvency]
-
A.
relationshipToPármeno
Indicates the specific type of personal or social relationship that one entity has to Pármeno.
-
B.
relationshipToEva
Indicates a specified type of personal or social relationship that an entity has with Eva.
-
C.
relationshipToBoris
Indicates the specific type of personal or social relationship that one entity has with Boris.
-
D.
relationshipToBéralde
Indicates the type or nature of a person or entity’s relationship to Béralde.
-
E.
relationshipToBartholomew
Indicates the specific type of relationship or connection an entity has to the individual named Bartholomew.
- 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_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 8:55 p.m.