Triple
T21532111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dragan Džajić |
E531255
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Dragan Džajić |
—
|
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: Dragan Džajić | Statement: [Dragan Džajić, name, Dragan Džajić]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dragan Džajić Context triple: [Dragan Džajić, name, Dragan Džajić]
-
A.
Dragan Džajić
chosen
Dragan Džajić is a legendary Serbian (Yugoslav) footballer widely regarded as one of the greatest left wingers in European football history.
-
B.
Dragan Kićanović
Dragan Kićanović is a former Yugoslav basketball star widely regarded as one of Europe’s greatest shooting guards of the 1970s and early 1980s.
-
C.
Mlađan Dinkić
Mlađan Dinkić is a Serbian economist and politician known for serving in several high-ranking government positions, including roles in economic and financial policymaking.
-
D.
Đorđe Milićević
Đorđe Milićević is a Serbian politician who has held senior leadership roles within the Socialist Party of Serbia and served in the National Assembly of Serbia.
-
E.
Branko Đurić
Branko Đurić is a Bosnian actor, comedian, and director best known internationally for his role in the Oscar-winning war film "No Man's Land."
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0a0e7c8190bbb7ed5c4dfe33af |
completed | April 26, 2026, 11:17 p.m. |
Created at: April 16, 2026, 6:27 p.m.