Triple
T6240411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mykolaiv |
E139584
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Mykolayiv |
E139584
|
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: Mykolayiv | Statement: [Mykolaiv, hasAlternativeName, Mykolayiv]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mykolayiv Context triple: [Mykolaiv, hasAlternativeName, Mykolayiv]
-
A.
Mykolaiv
chosen
Mykolaiv is a major shipbuilding and industrial city in southern Ukraine located near the Black Sea.
-
B.
Kremenchuk
Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
-
C.
Odesa
Odesa is a major port city on the Black Sea in southern Ukraine, known for its historic architecture, multicultural heritage, and key economic and cultural role in the country.
-
D.
Myrhorod
Myrhorod is a historic city in central Ukraine, known for its mineral springs and as the setting of several stories by writer Nikolai Gogol.
-
E.
Dnipro
Dnipro is one of Ukraine’s largest industrial and cultural centers, located on the Dnieper River in the central-eastern part of the country.
- 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063067d9c819085a18d9d03939266 |
completed | March 22, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5190e0a6481909e5372334a851770 |
completed | March 26, 2026, 11:31 a.m. |
Created at: March 22, 2026, 4:23 p.m.