Triple
T2027159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Livadia, Crimea |
E44433
|
entity |
| Predicate | nearbySettlement |
P350
|
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: [Livadia, Crimea, nearbySettlement, Koreiz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koreiz Context triple: [Livadia, Crimea, nearbySettlement, Koreiz]
-
A.
Koreiz
chosen
Koreiz is a resort settlement on the southern coast of Crimea, known for its seaside location and historic villas.
-
B.
Kōkyo
Kōkyo is the primary residence of Japan’s Emperor, a historic palace complex and gardens located in central Tokyo.
-
C.
Seoni
Seoni is a town and district headquarters in the central Indian state of Madhya Pradesh, known for its proximity to Pench National Park and its association with Rudyard Kipling’s "The Jungle Book."
-
D.
Kikuchi
Kikuchi is a Japanese surname borne by various notable individuals across fields such as acting, sports, and academia.
-
E.
Kamen
Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
- 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_69a889144f2481909932f0746a93023d |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb911e5dc819097e40af0da4d01e7 |
completed | March 7, 2026, 5:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1fead86c8190b3b247e88aad30f9 |
completed | March 9, 2026, 1:18 a.m. |
Created at: March 4, 2026, 7:38 p.m.