Triple
T14242333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viscountess Beaconsfield |
E353040
|
entity |
| Predicate | titleHolderMaritalStatus |
P5173
|
FINISHED |
| Object | married to Benjamin Disraeli |
—
|
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 Benjamin Disraeli | Statement: [Viscountess Beaconsfield, titleHolderMaritalStatus, married to Benjamin Disraeli]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleHolderMaritalStatus Context triple: [Viscountess Beaconsfield, titleHolderMaritalStatus, married to Benjamin Disraeli]
-
A.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
B.
spouseStatus
chosen
Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
-
C.
hasCivilStatus
Indicates the civil or marital status that applies to a person or entity (e.g., single, married, divorced).
-
D.
spouseStatusAtMarriage
Indicates the marital status each partner held at the time their marriage to one another was formed.
-
E.
hasMaritalStatusAtEnd
Indicates that an entity possesses a specific marital status at the end of a given period, event, or reference time.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6244ad188190b9d9db7914240410 |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:08 a.m.