Triple
T1381581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emden |
E29348
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Cherepovets
Cherepovets is a major industrial city in northwestern Russia, known especially for its large steel production and chemical industries.
|
E217616
|
NE FINISHED |
How this triple was built (4 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: Cherepovets | Statement: [Emden, hasTwinTown, Cherepovets]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cherepovets Context triple: [Emden, hasTwinTown, Cherepovets]
-
A.
Elektrostal
Elektrostal is an industrial city in Russia known for its metallurgical and engineering industries, located east of Moscow.
-
B.
Tomsk
Tomsk is a historic university and research city in southwestern Siberia, known as one of the region’s oldest and most important cultural and educational centers.
-
C.
Kostroma
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.
-
D.
Dmitrov
Dmitrov is a historic town in Moscow Oblast, Russia, located north of Moscow and known for its medieval kremlin and role as a regional cultural 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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cherepovets Triple: [Emden, hasTwinTown, Cherepovets]
Generated description
Cherepovets is a major industrial city in northwestern Russia, known especially for its large steel production and chemical industries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cherepovets Target entity description: Cherepovets is a major industrial city in northwestern Russia, known especially for its large steel production and chemical industries.
-
A.
Elektrostal
Elektrostal is an industrial city in Russia known for its metallurgical and engineering industries, located east of Moscow.
-
B.
Tomsk
Tomsk is a historic university and research city in southwestern Siberia, known as one of the region’s oldest and most important cultural and educational centers.
-
C.
Kostroma
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.
-
D.
Dmitrov
Dmitrov is a historic town in Moscow Oblast, Russia, located north of Moscow and known for its medieval kremlin and role as a regional cultural 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. chosen
Provenance (5 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c31b176c8190a896183140c5c8be |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3ae387c8190b72ca26ab81a53b6 |
completed | March 8, 2026, 10:09 p.m. |
| NEDg | Description generation | batch_69adf55207248190bd903c7faa3729e7 |
completed | March 8, 2026, 10:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adf5e074088190b6b383fb93cd18d8 |
completed | March 8, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:59 p.m.