Triple
T30807119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrei Vladimirovich Romanov |
E784532
|
entity |
| Predicate | spouseLaterCitizenship |
P88886
|
FINISHED |
| Object | France |
—
|
NE NERFINISHED |
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: France | Statement: [Andrei Vladimirovich Romanov, spouseLaterCitizenship, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseLaterCitizenship Context triple: [Andrei Vladimirovich Romanov, spouseLaterCitizenship, France]
-
A.
spouseLaterNationality
Indicates that a person’s spouse held or acquired a particular nationality at a later point in time than the reference period.
-
B.
spouseCountryOfCitizenship
Indicates the country in which a person's spouse holds legal citizenship.
-
C.
citizenshipStatusAfterMarriage
Indicates the change or resulting state of a person's citizenship that occurs as a consequence of their marriage.
-
D.
spouseNaturalisationCountry
chosen
Indicates the country in which a person’s spouse obtained citizenship through naturalisation.
-
E.
residenceDuringLaterYearsOfSpouse
Indicates that an entity lived in a particular place during the later years of their spouse’s life.
- 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_69f224b3a7ec819096939414d103e31e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
Created at: April 29, 2026, 8:43 p.m.