Triple
T33878097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. John Graham Bretton |
E868409
|
entity |
| Predicate | relationshipTypeWithLucySnowe |
P206714
|
FINISHED |
| Object | close friend |
—
|
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: close friend | Statement: [Dr. John Graham Bretton, relationshipTypeWithLucySnowe, close friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithLucySnowe Context triple: [Dr. John Graham Bretton, relationshipTypeWithLucySnowe, close friend]
-
A.
relationshipToJaneEyre
Indicates the specific familial, social, or emotional connection that one entity has to Jane Eyre.
-
B.
relationshipToIsabellaLinton
Indicates the specific familial, social, or emotional relationship that one entity has with Isabella Linton.
-
C.
relationshipTypeWithMargaretSchlegel
Indicates the specific type or nature of the relationship that an entity has with Margaret Schlegel.
-
D.
relationshipTypeWithHelenSchlegel
Indicates the specific nature or category of relationship that an entity has with Helen Schlegel.
-
E.
relationshipToEdgarLinton
Indicates the nature or type of relationship an entity has with Edgar Linton.
- 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_69f34995b81c8190acdb45cea5a10eff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037e07fe4481909ca21eae7a941ee7 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:48 a.m.