Triple
T16182451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veselin Topalov |
E392717
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Ruse, Bulgaria |
E70722
|
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: Ruse, Bulgaria | Statement: [Veselin Topalov, placeOfBirth, Ruse, Bulgaria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruse, Bulgaria Context triple: [Veselin Topalov, placeOfBirth, Ruse, Bulgaria]
-
A.
Ruse
Ruse is a residential suburb in the Macarthur region of Sydney, New South Wales, Australia.
-
B.
Ruse
chosen
Ruse is a major Bulgarian city and river port on the Danube, known for its elegant architecture and role as an important economic and transport hub.
-
C.
Pazardzhik, Bulgaria
Pazardzhik is a city in southern Bulgaria known as a regional administrative and cultural center on the banks of the Maritsa River.
-
D.
Reutov
Reutov is a town in western Russia that functions as a suburban satellite of Moscow, known for its residential areas and proximity to the capital.
-
E.
Varna
Varna is a major Bulgarian city on the Black Sea coast known as an important economic, cultural, and maritime center.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205ef39081908da383abdebc2ccc |
completed | April 17, 2026, 11:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffff03400481908e66db8cf0213c15 |
completed | May 10, 2026, 3:44 a.m. |
Created at: April 10, 2026, 5:02 a.m.