Triple
T589472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Coast of Crimea |
E17234
|
entity |
| Predicate | hasMajorResort |
P10436
|
FINISHED |
| Object | Koreiz |
E67751
|
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: Koreiz | Statement: [Southern Coast of Crimea, hasMajorResort, Koreiz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koreiz Context triple: [Southern Coast of Crimea, hasMajorResort, Koreiz]
-
A.
Koreiz
chosen
Koreiz is a resort settlement on the southern coast of Crimea, known for its seaside location and historic villas.
-
B.
Kamen
Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
-
C.
Tenjin
Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
-
D.
Kitchawan
Kitchawan is a small hamlet within the town of Yorktown in Westchester County, New York, known for its residential character and proximity to natural areas.
-
E.
Shimamoto
Shimamoto is a town in Osaka Prefecture, Japan, located between Kyoto and Osaka along the Yodo River.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49d2a5f5481908bb9a71ff0f534d4 |
completed | March 1, 2026, 8:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a55a734f6c8190a141dafc03dd2e77 |
completed | March 2, 2026, 9:37 a.m. |
Created at: March 1, 2026, 7:33 p.m.