Triple
T17416819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poltava Oblast |
E423510
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Myrhorod |
—
|
NE NERFINISHED |
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: Myrhorod | Statement: [Poltava Oblast, containsCity, Myrhorod]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myrhorod Context triple: [Poltava Oblast, containsCity, Myrhorod]
-
A.
Myrhorod
chosen
Myrhorod is a historic city in central Ukraine, known for its mineral springs and as the setting of several stories by writer Nikolai Gogol.
-
B.
Okhtyrka
Okhtyrka is a historic city in northeastern Ukraine known as one of the principal centers of the Sloboda Ukraine region.
-
C.
Nizhyn
Nizhyn is a historic city in northern Ukraine known for its cultural heritage, educational institutions, and well-preserved architecture.
-
D.
Khmilnyk
Khmilnyk is a spa and resort town in central Ukraine known for its radon mineral waters and therapeutic health facilities.
-
E.
Melitopol
Melitopol is a strategically important industrial and transportation hub in southeastern Ukraine, known for its agricultural production and key road and rail connections.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44232ecdc8190ac8958c1780fea19 |
completed | April 19, 2026, 2:47 a.m. |
Created at: April 10, 2026, 5:46 a.m.