Triple
T20100139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolly Oblonskaya |
E496511
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Darya |
—
|
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: Darya | Statement: [Dolly Oblonskaya, givenName, Darya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darya Context triple: [Dolly Oblonskaya, givenName, Darya]
-
A.
Darya
chosen
Darya is a feminine given name most notably borne by Belarusian biathlete and Olympic champion Darya Domracheva.
-
B.
Turano River
The Turano River is a watercourse in central Italy that flows through the Lazio region, forming the Turano Lake reservoir and passing near towns such as Colle di Tora.
-
C.
Amudarya
Amudarya is a town and district-level administrative center in the autonomous Republic of Karakalpakstan in northwestern Uzbekistan.
-
D.
Abakan
Abakan is a city in south-central Siberia, Russia, serving as the administrative, economic, and cultural center of the Republic of Khakassia.
-
E.
Kara Darya
Kara Darya is a major river in Central Asia that flows through Kyrgyzstan and Uzbekistan, helping to form the Syr Darya and irrigate the fertile Ferghana Valley.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6666f2298819089659f13556ca305 |
completed | April 20, 2026, 5:46 p.m. |
Created at: April 11, 2026, 11:26 p.m.