Triple
T17313218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shumerlya |
E420352
|
entity |
| Predicate | hasRailwayConnection |
P13914
|
FINISHED |
| Object |
Kanash
Kanash is a town in the Chuvash Republic of Russia known as a significant regional railway junction and transport hub.
|
E1283882
|
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: Kanash | Statement: [Shumerlya, hasRailwayConnection, Kanash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kanash Context triple: [Shumerlya, hasRailwayConnection, Kanash]
-
A.
Kyotanabe
Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
-
B.
Ishkashimi
Ishkashimi is a lesser-known Eastern Iranian language spoken by small communities in parts of Afghanistan and Tajikistan.
-
C.
Kasukabe
Kasukabe is a city in Japan known for its suburban character within the Greater Tokyo area and as the setting of the popular manga and anime series "Crayon Shin-chan."
-
D.
Kōta
Kōta is a town in central Japan known for its manufacturing industries and location within Aichi Prefecture.
-
E.
Hadano
Hadano is a city in Kanagawa Prefecture, Japan, known for its natural scenery, hiking trails, and proximity to the Tanzawa Mountains.
- 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: Kanash Triple: [Shumerlya, hasRailwayConnection, Kanash]
Generated description
Kanash is a town in the Chuvash Republic of Russia known as a significant regional railway junction and transport hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kanash Target entity description: Kanash is a town in the Chuvash Republic of Russia known as a significant regional railway junction and transport hub.
-
A.
Kyotanabe
Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
-
B.
Ishkashimi
Ishkashimi is a lesser-known Eastern Iranian language spoken by small communities in parts of Afghanistan and Tajikistan.
-
C.
Kasukabe
Kasukabe is a city in Japan known for its suburban character within the Greater Tokyo area and as the setting of the popular manga and anime series "Crayon Shin-chan."
-
D.
Kōta
Kōta is a town in central Japan known for its manufacturing industries and location within Aichi Prefecture.
-
E.
Hadano
Hadano is a city in Kanagawa Prefecture, Japan, known for its natural scenery, hiking trails, and proximity to the Tanzawa Mountains.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4399a4194819091d34cd3fffc8072 |
completed | April 19, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02300a90d08190910c871f1f323348 |
completed | May 11, 2026, 7:37 p.m. |
| NEDg | Description generation | batch_6a02309eb7ac81908133a41136fbaac5 |
completed | May 11, 2026, 7:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a02313b69888190935d7c95ab273ec1 |
completed | May 11, 2026, 7:42 p.m. |
Created at: April 10, 2026, 5:43 a.m.