Triple
T4038049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgi Plekhanov |
E83874
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Georgi |
E400091
|
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: Georgi | Statement: [Georgi Plekhanov, givenName, Georgi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georgi Context triple: [Georgi Plekhanov, givenName, 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.
Theodore Svetoslav
Theodore Svetoslav was a medieval Bulgarian tsar who restored and strengthened the Second Bulgarian Empire in the early 14th century through military successes and internal consolidation.
-
C.
Mario Grigorov
Mario Grigorov is a Bulgarian-born composer and pianist best known for his film scores and collaborations with director Lee Daniels.
-
D.
Georgy
Georgy is a masculine given name of Russian origin, notably borne by Soviet military commander Georgy Zhukov.
-
E.
Alexander Toshev
Alexander Toshev is a computer scientist known for his contributions to computer vision and deep learning, including influential work on object detection.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb3656f08190aa5286d951013646 |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b55646e5d881909eadd0640a4f1796 |
completed | March 14, 2026, 12:36 p.m. |
Created at: March 9, 2026, 3:37 p.m.