Triple
T18053464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgi Todorov |
E431976
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Georgi |
—
|
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: Georgi | Statement: [Georgi Todorov, hasGivenName, Georgi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georgi Context triple: [Georgi Todorov, hasGivenName, Georgi]
-
A.
Georgi
chosen
Georgi is a common Bulgarian male given name, widely used across Slavic countries and derived from the Greek name Georgios.
-
B.
Georgy Georgiu
Georgy Georgiu is an actor known for his role in the Soviet adventure-comedy film "Gentlemen of Fortune."
-
C.
Georgii
Georgii is a masculine given name, commonly used in Slavic countries as a variant of George.
-
D.
Lyuben
Lyuben is a masculine given name of Slavic origin, commonly used in Bulgaria and other Slavic countries.
-
E.
Kimon Georgiev
Kimon Georgiev was a Bulgarian military officer and politician who twice served as prime minister and played a leading role in several coups that reshaped Bulgaria’s 20th-century political landscape.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4c100e7e4819084470c5b7fced334 |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 10:26 a.m.