Triple
T4523536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Marya Bolkonskaya |
E103322
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marya |
E370383
|
NE 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: Marya | Statement: [Princess Marya Bolkonskaya, givenName, Marya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marya Context triple: [Princess Marya Bolkonskaya, givenName, Marya]
-
A.
Marya
chosen
Marya is a feminine given name, often considered a variant of Mary and used in various cultures and languages.
-
B.
Yehenara
Yehenara was a prominent Manchu noble clan of the Qing dynasty, best known as the family of Empress Dowager Cixi.
-
C.
Romeyka
Romeyka is an endangered Greek dialect spoken mainly in northeastern Turkey, notable for preserving many archaic features of Ancient Greek.
-
D.
Sharya
Sharya is a town in Kostroma Oblast, Russia, known as a regional railway junction and logging center.
-
E.
Marisa
Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd574d7c2481909049955ca47613a6 |
completed | March 20, 2026, 2:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bda440e104819095d84fcd183c7a44 |
completed | March 20, 2026, 7:47 p.m. |
Created at: March 20, 2026, 1:02 p.m.