Triple
T10170047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skopinsky Uyezd |
E235306
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Skopin |
E472492
|
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: Skopin | Statement: [Skopinsky Uyezd, namedAfter, Skopin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skopin Context triple: [Skopinsky Uyezd, namedAfter, Skopin]
-
A.
Skopin
chosen
Skopin is a historic town in western Russia known for its traditional pottery and ceramics industry.
-
B.
Skoparnik
Skoparnik is one of the main peaks of Bulgaria’s Vitosha Mountain, known for its hiking routes and panoramic views over the Sofia region.
-
C.
Kopaska
Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
-
D.
Skorba
Skorba is an archaeological temple site in Malta, notable for its prehistoric megalithic structures that form part of the island’s ancient temple complex heritage.
-
E.
Skodje
Skodje is a village and former municipality in western Norway, known for its scenic fjord landscape and historic stone arch bridge.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9d36608190be78665cc3410cf2 |
completed | April 2, 2026, 4:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d32acbd9ec81908849b17d8ba1dd11 |
completed | April 6, 2026, 3:38 a.m. |
Created at: March 30, 2026, 9:10 p.m.