Triple
T33620071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferdinand von Walter |
E861239
|
entity |
| Predicate | relationshipTypeWithLuise Miller |
P205243
|
FINISHED |
| Object | romantic love |
—
|
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: romantic love | Statement: [Ferdinand von Walter, relationshipTypeWithLuise Miller, romantic love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithLuise Miller Context triple: [Ferdinand von Walter, relationshipTypeWithLuise Miller, romantic love]
-
A.
socialStatusDifferenceWithLuise Miller
Indicates that there is a difference in social status between the subject and Luise Miller.
-
B.
relationshipTypeWithLuciousLyon
Indicates the specific nature or category of relationship that an entity has with Lucious Lyon.
-
C.
relationshipTypeWithLouisLitt
Indicates the specific nature or category of relationship that an entity has with Louis Litt.
-
D.
hasRelationshipTypeWith Alexandra Bergson
Indicates that there exists a specific type or category of relationship between an entity and Alexandra Bergson.
-
E.
haveRelationshipWith
Indicates that one entity is in some form of defined relationship or association with another entity.
- 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_69f34980fabc81909819228729a9ca84 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:41 a.m.