Triple
T16699568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proskuriv |
E405807
|
entity |
| Predicate | hasHistoricalNameForm |
P66486
|
FINISHED |
| Object | Proskurov |
E935102
|
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: Proskurov | Statement: [Proskuriv, hasHistoricalNameForm, Proskurov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Proskurov Context triple: [Proskuriv, hasHistoricalNameForm, Proskurov]
-
A.
Proskurov
chosen
Proskurov is the former name of the Ukrainian city now known as Khmelnytskyi, a regional center in western Ukraine.
-
B.
Zbarazh
Zbarazh is a historic town in western Ukraine known for its medieval castle and role in regional political and military history.
-
C.
Pavlohrad
Pavlohrad is an industrial city in central-eastern Ukraine known for its coal mining, chemical industry, and role as a regional transport hub.
-
D.
Chervonohrad
Chervonohrad is a mining and industrial city in western Ukraine known for its coal industry and location in the Lviv Oblast.
-
E.
Zhovkva
Zhovkva is a historic town in western Ukraine known for its well-preserved Renaissance architecture and multicultural heritage.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e383300d108190911e3cba8e07f2dd |
completed | April 18, 2026, 1:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b27dcef481909ccfe4d3d604b1de |
completed | May 10, 2026, 4:29 p.m. |
Created at: April 10, 2026, 5:19 a.m.