Triple
T4938148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bay of Kotor |
E110862
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Tivat |
E450141
|
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: Tivat | Statement: [Bay of Kotor, hasPart, Tivat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tivat Context triple: [Bay of Kotor, hasPart, Tivat]
-
A.
Tivat
chosen
Tivat is a coastal town in Montenegro known for its luxury marina Porto Montenegro and proximity to the Bay of Kotor.
-
B.
Milna
Milna is a picturesque coastal village and harbor town on the western side of the Croatian island of Brač, known for its traditional stone architecture and sheltered bay.
-
C.
Tivissa
Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
-
D.
Senja
Senja is Norway’s second-largest island, renowned for its dramatic coastal mountains, fishing villages, and scenic Arctic landscapes.
-
E.
Tiba
Tiba is a modern planned city in Egypt’s Luxor Governorate, developed to accommodate population growth and support regional economic and urban expansion.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70872270819080769dad972681ef |
completed | March 20, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be77bcb8d881908d393223bdea145a |
completed | March 21, 2026, 10:49 a.m. |
Created at: March 20, 2026, 1:31 p.m.