Triple
T20502203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonard Bast |
E503331
|
entity |
| Predicate | relationshipTypeWithHelenSchlegel |
P140328
|
FINISHED |
| Object | romantic involvement |
—
|
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: romantic involvement | Statement: [Leonard Bast, relationshipTypeWithHelenSchlegel, romantic involvement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithHelenSchlegel Context triple: [Leonard Bast, relationshipTypeWithHelenSchlegel, romantic involvement]
-
A.
relationshipWithIsabelArcher
Indicates that there exists a specific kind of interpersonal relationship or connection between an entity and Isabel Archer.
-
B.
relationshipToElinorDashwood
Indicates the specific familial, social, or interpersonal connection that one entity has to Elinor Dashwood.
-
C.
relationshipToLucyHoneychurch
Indicates the specific type of relationship or connection an entity has to Lucy Honeychurch.
-
D.
relationshipToIsabelArcher
Indicates the specific personal or social connection that an entity has to Isabel Archer.
-
E.
relationshipToHollyGolightly
Indicates the nature or type of relationship an entity has with Holly Golightly.
- 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.