Triple
T10365737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lydia Bennet |
E244245
|
entity |
| Predicate | relationshipToJaneBennet |
P93593
|
FINISHED |
| Object | younger sister |
—
|
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: younger sister | Statement: [Lydia Bennet, relationshipToJaneBennet, younger sister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToJaneBennet Context triple: [Lydia Bennet, relationshipToJaneBennet, younger sister]
-
A.
relationshipToCatherine
Indicates the specific familial, social, or interpersonal connection that one entity has to the person named Catherine.
-
B.
MaryRelationshipToElizabeth
Indicates a relational connection or association that Mary has toward Elizabeth, without specifying the exact nature of that relationship.
-
C.
relationshipToAnneBoleyn
Indicates the specific familial, marital, or social connection that an entity has to Anne Boleyn.
-
D.
relationshipTypeWithBertieWooster
Indicates the specific nature or category of relationship an entity has with Bertie Wooster.
-
E.
relationshipToBertieWooster
Indicates the specific type of personal or social relationship an entity has with Bertie Wooster.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e96f25f48190a41c8b0206b9238c |
completed | April 7, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69d4dface5508190a7b42f01ad0a19a2 |
completed | April 7, 2026, 10:42 a.m. |
| PDg | Predicate description generation | batch_69d4e944fac4819093b0312aa0efd729 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, noon