Triple
T36407042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caroline Beaufort Frankenstein |
E896773
|
entity |
| Predicate | relationshipToAlphonseFrankenstein |
P204860
|
FINISHED |
| Object | wife |
—
|
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: wife | Statement: [Caroline Beaufort Frankenstein, relationshipToAlphonseFrankenstein, wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAlphonseFrankenstein Context triple: [Caroline Beaufort Frankenstein, relationshipToAlphonseFrankenstein, wife]
-
A.
relationshipToAlceste
Indicates the type or nature of a subject’s relationship or connection to the entity Alceste.
-
B.
relationshipToLenore
Indicates the nature or type of relationship an entity has with Lenore.
-
C.
relationshipToBaudelaires
Indicates the type of personal or familial connection an entity has to the Baudelaires.
-
D.
relationshipToEthanEdwards
Indicates the nature or type of connection, association, or bond that one entity has with Ethan Edwards.
-
E.
relationshipToThérèse Raquin
Indicates the specific type of relationship or connection an entity has to Thérèse Raquin.
- 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_69f76e53b81081908d3b81860593f38a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:10 p.m.