Triple
T17073235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalmius River |
E414274
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object |
Kalmius
Kalmius is a river in eastern Ukraine that flows through the Donetsk region into the Sea of Azov.
|
E1249546
|
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: Kalmius | Statement: [Kalmius River, hasNameInLanguage, Kalmius]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kalmius Context triple: [Kalmius River, hasNameInLanguage, Kalmius]
-
A.
Torgos
Torgos is a genus of large Old World vultures best known for including the lappet-faced vulture.
-
B.
Tikhon
Tikhon was the religious name of Patriarch Tikhon of Moscow, the early 20th-century head of the Russian Orthodox Church known for leading it through the turmoil of the Russian Revolution and early Soviet period.
-
C.
Kologriv
Kologriv is a small historic town in Kostroma Oblast, Russia, known for its traditional wooden architecture and location within a forested, sparsely populated region.
-
D.
Khovrino
Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
-
E.
Virganskaya
Virganskaya is a Russian surname most notably borne by Irina Virganskaya, the daughter of former Soviet leader Mikhail Gorbachev.
- 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: Kalmius Triple: [Kalmius River, hasNameInLanguage, Kalmius]
Generated description
Kalmius is a river in eastern Ukraine that flows through the Donetsk region into the Sea of Azov.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kalmius Target entity description: Kalmius is a river in eastern Ukraine that flows through the Donetsk region into the Sea of Azov.
-
A.
Torgos
Torgos is a genus of large Old World vultures best known for including the lappet-faced vulture.
-
B.
Tikhon
Tikhon was the religious name of Patriarch Tikhon of Moscow, the early 20th-century head of the Russian Orthodox Church known for leading it through the turmoil of the Russian Revolution and early Soviet period.
-
C.
Kologriv
Kologriv is a small historic town in Kostroma Oblast, Russia, known for its traditional wooden architecture and location within a forested, sparsely populated region.
-
D.
Khovrino
Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
-
E.
Virganskaya
Virganskaya is a Russian surname most notably borne by Irina Virganskaya, the daughter of former Soviet leader Mikhail Gorbachev.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbc28fec81909c39d432094d9cdd |
completed | April 18, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ede108881909ddd0455be53ffac |
completed | May 11, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_6a012fe2a1b081909483baef845cc2c1 |
completed | May 11, 2026, 1:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0130c2ad9881909d8a8b64ebb59aa6 |
completed | May 11, 2026, 1:28 a.m. |
Created at: April 10, 2026, 5:34 a.m.