Triple
T33878377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellen Nussey |
E868417
|
entity |
| Predicate | relationshipToCharlotteBrontë |
P206715
|
FINISHED |
| Object | lifelong intimate 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: lifelong intimate friend | Statement: [Ellen Nussey, relationshipToCharlotteBrontë, lifelong intimate friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToCharlotteBrontë Context triple: [Ellen Nussey, relationshipToCharlotteBrontë, lifelong intimate friend]
-
A.
relationshipToJaneEyre
Indicates the specific familial, social, or emotional connection that one entity has to Jane Eyre.
-
B.
relationshipToCharlotteCharles
Indicates the specific type of relationship or connection an entity has to Charlotte Charles.
-
C.
relationshipToCatherineLinton
Indicates the specific familial or social relationship that an entity has to Catherine Linton.
-
D.
relationshipToIsabellaLinton
Indicates the specific familial, social, or emotional relationship that one entity has with Isabella Linton.
-
E.
literaryRelationship
Indicates a relationship between entities that are connected through literature, such as authorship, influence, adaptation, or other text-based associations.
- 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.