Triple
T4452949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marlene Dietrich |
E97654
|
entity |
| Predicate | yearOfNaturalization |
P11301
|
FINISHED |
| Object | 1939 |
—
|
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: 1939 | Statement: [Marlene Dietrich, yearOfNaturalization, 1939]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfNaturalization Context triple: [Marlene Dietrich, yearOfNaturalization, 1939]
-
A.
citizenshipGrantedYear
chosen
Indicates the specific year in which an entity was officially granted citizenship.
-
B.
yearOfImmigration
Indicates the specific year in which an entity immigrated to a new country or region.
-
C.
yearOfPermanentResidency
Indicates the specific year in which an entity began or was granted permanent residency in a particular place.
-
D.
laterCitizenship
Indicates that an entity acquired citizenship in a country or polity at a later point in time, after some earlier status or affiliation.
-
E.
dateOfCitizenshipChange
Indicates the date on which an entity’s citizenship status was changed from one nationality to another.
- 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_69b3454777808190b78aa9047ba1f018 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355f49dc081908727af81b886c08d |
completed | March 13, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69b34f649df081909d3cc2f6a1b8f282 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:33 p.m.