Triple
T25905485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mae Scriven |
E652738
|
entity |
| Predicate | marriedToDuringPeriod |
P78262
|
FINISHED |
| Object | early 1930s |
—
|
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: early 1930s | Statement: [Mae Scriven, marriedToDuringPeriod, early 1930s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToDuringPeriod Context triple: [Mae Scriven, marriedToDuringPeriod, early 1930s]
-
A.
maritalPeriodWith
chosen
Indicates the time span during which two entities were married to each other.
-
B.
marriagePeriodWith
Indicates the time span during which two entities were married to each other.
-
C.
marriedOn
Indicates that a marriage event took place on a specific date for the related entities.
-
D.
marriedToDuringOffice
Indicates that one person was married to another person specifically during the time they held a particular office or position.
-
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_69e7ab3d3f8481909bc53ed64c06af33 |
completed | April 21, 2026, 4:52 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 22, 2026, 8:27 a.m.