Triple
T15390813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amy Dubanowski |
E368037
|
entity |
| Predicate | maritalStatusLaterInSeries |
P20884
|
FINISHED |
| Object | separated |
—
|
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: separated | Statement: [Amy Dubanowski, maritalStatusLaterInSeries, separated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritalStatusLaterInSeries Context triple: [Amy Dubanowski, maritalStatusLaterInSeries, separated]
-
A.
hasMaritalStatusAtEnd
Indicates that an entity possesses a specific marital status at the end of a given period, event, or reference time.
-
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.
hasMaritalStatusAfterFirstMarriage
Indicates that an entity’s marital status at a given time is the one it holds after its first marriage has occurred.
-
D.
characterMaritalHistory
Indicates a relationship that records the sequence of a character’s past and present marital relationships, including spouses and relevant time periods.
-
E.
socialStatusAfterMarriage
Indicates the social status an individual holds as a result of, or following, their marriage.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e7727a081908eff45bbc1633c8a |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.