Triple
T14090761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snezhnaya River |
E339123
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object |
Снежная
Снежная is a river in Russia known for flowing through the Siberian region and contributing to the local freshwater system and ecosystems.
|
E1080252
|
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: Снежная | Statement: [Snezhnaya River, hasNameInLanguage, Снежная]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Снежная Context triple: [Snezhnaya River, hasNameInLanguage, Снежная]
-
A.
Śnieżnica
Śnieżnica is a mountain peak in southern Poland, located in the Beskid Wyspowy range and popular for hiking and winter sports.
-
B.
Blizne
Blizne is a village in southeastern Poland best known for its historic wooden All Saints Church, a UNESCO World Heritage Site.
-
C.
Śnieżka
Śnieżka is a prominent mountain peak on the border of Poland and the Czech Republic, renowned as the tallest summit in the Sudetes range and a popular hiking destination.
-
D.
Śnieżnik
Śnieżnik is a prominent mountain on the Polish–Czech border, known for its scenic alpine landscapes and popular hiking trails.
-
E.
Snoge
Snoge is the historic 17th-century Portuguese-Israelite synagogue in Amsterdam, renowned as one of the oldest and best-preserved Sephardic synagogues in Europe.
- 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: Снежная Triple: [Snezhnaya River, hasNameInLanguage, Снежная]
Generated description
Снежная is a river in Russia known for flowing through the Siberian region and contributing to the local freshwater system and ecosystems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Снежная Target entity description: Снежная is a river in Russia known for flowing through the Siberian region and contributing to the local freshwater system and ecosystems.
-
A.
Śnieżnica
Śnieżnica is a mountain peak in southern Poland, located in the Beskid Wyspowy range and popular for hiking and winter sports.
-
B.
Blizne
Blizne is a village in southeastern Poland best known for its historic wooden All Saints Church, a UNESCO World Heritage Site.
-
C.
Śnieżka
Śnieżka is a prominent mountain peak on the border of Poland and the Czech Republic, renowned as the tallest summit in the Sudetes range and a popular hiking destination.
-
D.
Śnieżnik
Śnieżnik is a prominent mountain on the Polish–Czech border, known for its scenic alpine landscapes and popular hiking trails.
-
E.
Snoge
Snoge is the historic 17th-century Portuguese-Israelite synagogue in Amsterdam, renowned as one of the oldest and best-preserved Sephardic synagogues in Europe.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5ee3213c8190af2853a2a5b302a2 |
completed | April 14, 2026, 3:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd0a7aab88190949cf1fd8e11b050 |
completed | May 7, 2026, 5:49 p.m. |
| NEDg | Description generation | batch_69fcd5ad82388190a196d811734cdca2 |
completed | May 7, 2026, 6:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fcd63a114881909ff7b2df937d24df |
completed | May 7, 2026, 6:13 p.m. |
Created at: April 9, 2026, 10:21 p.m.