Triple
T5326194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgy Gapon |
E123191
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Georgy |
E97024
|
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: Georgy | Statement: [Georgy Gapon, givenName, Georgy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georgy Context triple: [Georgy Gapon, givenName, Georgy]
-
A.
Georgy
chosen
Georgy is a masculine given name of Russian origin, notably borne by Soviet military commander Georgy Zhukov.
-
B.
Georgi
Georgi is a common Bulgarian male given name, widely used across Slavic countries and derived from the Greek name Georgios.
-
C.
Alek
Alek is a common diminutive or short form of the given name Aleksander, used in various Slavic and European languages.
-
D.
Sergei
Sergei is a masculine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
E.
Georges
Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
- 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85912d24819093cc405bebe8e870 |
completed | March 20, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf21bba3f8819085efcb9d75fea1f9 |
completed | March 21, 2026, 10:54 p.m. |
Created at: March 20, 2026, 1:59 p.m.