Triple
T15629878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marfa Sobakina |
E375782
|
entity |
| Predicate | spouseOfMonarchRank |
P88104
|
FINISHED |
| Object | Tsar of Russia |
—
|
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: Tsar of Russia | Statement: [Marfa Sobakina, spouseOfMonarchRank, Tsar of Russia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfMonarchRank Context triple: [Marfa Sobakina, spouseOfMonarchRank, Tsar of Russia]
-
A.
spouseIsMonarchOf
chosen
Indicates that a person's spouse holds the position of monarch (ruler) of a specified country or territory.
-
B.
spouseOfHeirToThrone
Indicates that one person is the married partner of an individual who is the heir to a throne.
-
C.
pairedInRoyalTitleWith
Indicates that two individuals are jointly named or associated together within the same royal title (e.g., as co-rulers, consorts, or title partners).
-
D.
marriedToFutureMonarch
Indicates that one person is married to another person who will become a monarch in the future.
-
E.
siblingOrConsort
Indicates that two entities are related either as siblings (sharing at least one parent) or as consorts (spouses/partners in a marital or analogous union).
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb536348190b93ed3c178d1ffb8 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.