Triple
T6742473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phyllis Livingston Potter |
E154118
|
entity |
| Predicate | hadPreviousMarriage |
P33258
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Phyllis Livingston Potter, hadPreviousMarriage, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPreviousMarriage Context triple: [Phyllis Livingston Potter, hadPreviousMarriage, yes]
-
A.
marriedBefore
chosen
Indicates that one entity entered into a marriage at an earlier time than the other entity.
-
B.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
C.
marriedAfter
Indicates that one marriage occurred later in time than another specified marriage.
-
D.
hasNotableMarriage
Indicates a marital relationship involving the subject that is considered significant or noteworthy in some context.
-
E.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of 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_69c6880d84d8819095d19de2295f26ac |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1b245988190a9d5260f4872bbea |
completed | March 27, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69c6d09067a0819087ed6c820f4699f8 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:10 p.m.