Triple
T31325566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eeva von Bock |
E798875
|
entity |
| Predicate | spouseCharacterTraitInFiction |
P91240
|
FINISHED |
| Object | idealistic |
—
|
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: idealistic | Statement: [Eeva von Bock, spouseCharacterTraitInFiction, idealistic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseCharacterTraitInFiction Context triple: [Eeva von Bock, spouseCharacterTraitInFiction, idealistic]
-
A.
spouseCharacterization
Indicates how one spouse describes, evaluates, or characterizes the other spouse within their relationship.
-
B.
spouseCharacteristic
chosen
Indicates that a particular characteristic, trait, or attribute is associated with a person’s spouse within the relationship.
-
C.
spouseCharacterOf
Indicates a marital relationship where one character is the spouse of another character.
-
D.
spouseOccupationInFiction
Indicates that a person’s spouse has a particular occupation within a fictional work or narrative context.
-
E.
spouseCharacterPlayed
Indicates that one entity is the spouse of the character portrayed by another entity.
- 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_69f224e3238c8190b2291f50ea4962cd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: April 29, 2026, 9:15 p.m.