Triple
T17720257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Livoberezhna |
E442314
|
entity |
| Predicate | precededByStation |
P29771
|
FINISHED |
| Object | Darnytsia |
—
|
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: Darnytsia | Statement: [Livoberezhna, precededByStation, Darnytsia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darnytsia Context triple: [Livoberezhna, precededByStation, Darnytsia]
-
A.
Darnytsia
chosen
Darnytsia is a station on the Kyiv Metro system in Ukraine, serving the Sviatoshynsko–Brovarska line on the city's left bank.
-
B.
Rubizhne
Rubizhne is an industrial city in eastern Ukraine known for its chemical and manufacturing industries and its location within the conflict-affected Donbas region.
-
C.
Pervomaiskyi
Pervomaiskyi is a small industrial city in eastern Ukraine known for its chemical industry and location within Kharkiv Oblast.
-
D.
Sosnytsia
Sosnytsia is a small historic town in northern Ukraine known for its traditional architecture and rural character.
-
E.
Vyrlytsia
Vyrlytsia is a station on the Kyiv Metro system in Ukraine.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4748520a881908dc3446d33236ff7 |
completed | April 19, 2026, 6:21 a.m. |
Created at: April 10, 2026, 10:07 a.m.