Triple
T12960837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorothea Brooke |
E310137
|
entity |
| Predicate | hasMaritalStatusAfterFirstMarriage |
P107706
|
FINISHED |
| Object | married to Edward Casaubon |
—
|
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: married to Edward Casaubon | Statement: [Dorothea Brooke, hasMaritalStatusAfterFirstMarriage, married to Edward Casaubon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritalStatusAfterFirstMarriage Context triple: [Dorothea Brooke, hasMaritalStatusAfterFirstMarriage, married to Edward Casaubon]
-
A.
marriedBefore
Indicates that one entity entered into a marriage at an earlier time than the other entity.
-
B.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
C.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
D.
spouseStatusAtMarriage
Indicates the marital status each partner held at the time their marriage to one another was formed.
-
E.
marriedAfter
Indicates that one marriage occurred later in time than another specified marriage.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97e5811f481908178fac6d2e0efcd |
completed | April 10, 2026, 10:48 p.m. |
Created at: April 9, 2026, 5:44 p.m.