Triple
T16991944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Branko Grünbaum |
E412213
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Branko |
E896604
|
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: Branko | Statement: [Branko Grünbaum, givenName, Branko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Branko Context triple: [Branko Grünbaum, givenName, Branko]
-
A.
Branko
chosen
Branko is a masculine given name commonly used in Slavic countries, particularly in the Balkans.
-
B.
Vlatko
Vlatko is a masculine given name commonly used in Slavic countries, particularly in North Macedonia and other parts of the Balkans.
-
C.
Dražan
Dražan is a masculine given name most notably borne by Croatian footballer and manager Dražan Jerković.
-
D.
Duško
Duško is the given name of Duško Tadić, a Bosnian Serb who became known as the first person tried by the International Criminal Tribunal for the former Yugoslavia for war crimes committed during the Bosnian War.
-
E.
Miljan
Miljan is a surname most notably borne by American film actor John Miljan, who appeared in numerous Hollywood productions from the silent era through the 1950s.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d283d2388190a78bf8d179e83fdc |
completed | April 18, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b433e688190ac8dda10638a197f |
completed | May 10, 2026, 11:56 p.m. |
Created at: April 10, 2026, 5:32 a.m.