Triple
T25650343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Father, Dear Father |
E643081
|
entity |
| Predicate | mainCharacterMaritalStatus |
P20884
|
FINISHED |
| Object | divorced |
—
|
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: divorced | Statement: [Father, Dear Father, mainCharacterMaritalStatus, divorced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterMaritalStatus Context triple: [Father, Dear Father, mainCharacterMaritalStatus, divorced]
-
A.
characterMaritalHistory
Indicates a relationship that records the sequence of a character’s past and present marital relationships, including spouses and relevant time periods.
-
B.
marital status
chosen
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
C.
fictionalMaritalStatus
Indicates that an entity has a marital status that exists only within a fictional, narrative, or hypothetical context rather than in real life.
-
D.
maritalStatusInDisguise
Indicates that an entity’s true marital status is being concealed or misrepresented, typically appearing different from what it actually is.
-
E.
maidenFamilyStatus
Indicates the family-related status or condition associated with a person in their maiden (pre-marriage) state.
- 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_69e77e7d8a848190a98d0162325fd780 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f638d11c988190af7fd4572b08e038 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f63706b6008190993577193c85ff50 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 21, 2026, 6:21 p.m.