Triple
T4455057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalmatia |
E97699
|
entity |
| Predicate | containsIsland |
P970
|
FINISHED |
| Object | Korčula |
E110307
|
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: Korčula | Statement: [Dalmatia, containsIsland, Korčula]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korčula Context triple: [Dalmatia, containsIsland, Korčula]
-
A.
Korčula
chosen
Korčula is a historic Adriatic island known for its medieval walled town, dense forests, and rich Croatian cultural heritage.
-
B.
Hvar
Hvar is a popular Croatian island in the Adriatic Sea known for its sunny climate, historic town, lavender fields, and vibrant nightlife.
-
C.
Trogir
Trogir is a historic coastal town in Croatia renowned for its well-preserved medieval architecture and UNESCO-listed old town on the Adriatic Sea.
-
D.
Brač
Brač is a large Adriatic island in Croatia known for its white-pebble Zlatni Rat beach and historic stone masonry.
-
E.
Makarska
Makarska is a coastal town and popular tourist resort on the Adriatic Sea in southern Croatia, known for its beaches and the nearby Biokovo mountain range.
- 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_69b3454777808190b78aa9047ba1f018 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355f79ca481909338dda9f4f7171f |
completed | March 13, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b67bae950c8190a9ef8a812d47bf8d |
completed | March 15, 2026, 9:28 a.m. |
Created at: March 12, 2026, 11:33 p.m.