Triple
T1983494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aachen |
E43082
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Kostroma |
E65483
|
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: Kostroma | Statement: [Aachen, hasTwinTown, Kostroma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kostroma Context triple: [Aachen, hasTwinTown, Kostroma]
-
A.
Kostroma
chosen
Kostroma is a historic Russian city northeast of Moscow, known as part of the Golden Ring and for its well-preserved medieval architecture and monasteries.
-
B.
Yaroslavl
Yaroslavl is a historic city in central Russia, located on the Volga River and known as one of the Golden Ring cities famed for its well-preserved medieval architecture and cultural heritage.
-
C.
Ryazan
Ryazan is a historic city in western Russia known for its medieval kremlin, role as a regional cultural and economic center, and legacy as one of the country’s oldest urban settlements.
-
D.
Penza
Penza is a city in western Russia known as a regional cultural and industrial center.
-
E.
Voronezh
Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb820815481908aac6d89b437225b |
completed | March 7, 2026, 5:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afce742d288190bfdcffb81c29a173 |
completed | March 10, 2026, 7:55 a.m. |
Created at: March 4, 2026, 7:37 p.m.