Triple
T5759291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fanny Dashwood |
E127047
|
entity |
| Predicate | relationshipToDashwoodSisters |
P28764
|
FINISHED |
| Object | sister-in-law |
—
|
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: sister-in-law | Statement: [Fanny Dashwood, relationshipToDashwoodSisters, sister-in-law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToDashwoodSisters Context triple: [Fanny Dashwood, relationshipToDashwoodSisters, sister-in-law]
-
A.
maritalRelations
Indicates a legally or socially recognized spousal relationship or marriage-based connection between two entities.
-
B.
MaryRelationshipToElizabeth
Indicates a relational connection or association that Mary has toward Elizabeth, without specifying the exact nature of that relationship.
-
C.
relationToNurJahan
Indicates a relationship or connection that an entity has specifically to Nur Jahan.
-
D.
relationshipWithSybilFawlty
Indicates the type or nature of a relationship that an entity has with Sybil Fawlty.
-
E.
familyOf
chosen
Indicates a familial relationship exists between the entities, such as by blood, marriage, or adoption.
- F. None of above.
Provenance (3 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_69c00833a3fc81908f4bc29ed011b7a6 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0293771ec8190a0082685327d649b |
completed | March 22, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69c021cc68648190bb86d049ebe80f12 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:49 p.m.