Triple
T20502205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonard Bast |
E503331
|
entity |
| Predicate | relationshipTypeWithMargaretSchlegel |
P140329
|
FINISHED |
| Object | beneficiary of concern |
—
|
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: beneficiary of concern | Statement: [Leonard Bast, relationshipTypeWithMargaretSchlegel, beneficiary of concern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithMargaretSchlegel Context triple: [Leonard Bast, relationshipTypeWithMargaretSchlegel, beneficiary of concern]
-
A.
relationshipToElinorDashwood
Indicates the specific familial, social, or interpersonal connection that one entity has to Elinor Dashwood.
-
B.
relationshipToMarianneDashwood
Indicates the specific familial, social, or emotional connection that an entity has to Marianne Dashwood.
-
C.
relationshipToJaneBennet
Indicates the specific familial, social, or emotional connection that one entity has to Jane Bennet.
-
D.
relationshipTypeWithBertieWooster
Indicates the specific nature or category of relationship an entity has with Bertie Wooster.
-
E.
relationshipToCatherine
Indicates the specific familial, social, or interpersonal connection that one entity has to the person named Catherine.
- 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dc272a481909329ecd1560989ef |
completed | April 20, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69e59fcdf6e08190a604204615dc56e6 |
completed | April 20, 2026, 3:38 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:35 a.m.