Triple
T15345216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulvik |
E366898
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object |
Tysso
Tysso is a river in the municipality of Ulvik in western Norway, known for flowing through a scenic fjord landscape.
|
E1151739
|
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: Tysso | Statement: [Ulvik, hasRiver, Tysso]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tysso Context triple: [Ulvik, hasRiver, Tysso]
-
A.
Tlass
Tlass is a Syrian family name most prominently associated with Mustafa Tlass, a long-serving defense minister under Hafez al-Assad.
-
B.
Thrylos
Thrylos is the popular nickname of Greek football club Olympiacos FC, reflecting its legendary status and storied success.
-
C.
Teurnia
Teurnia was an important ancient Roman city that served as a major administrative and cultural center in the province of Noricum, located in what is now southern Austria.
-
D.
Tarutyne
Tarutyne is an urban-type settlement in Odesa Oblast, southwestern Ukraine, serving as a local administrative and cultural center.
-
E.
Teisen
Teisen is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green spaces, and convenient access to public transportation.
- 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: Tysso Triple: [Ulvik, hasRiver, Tysso]
Generated description
Tysso is a river in the municipality of Ulvik in western Norway, known for flowing through a scenic fjord landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tysso Target entity description: Tysso is a river in the municipality of Ulvik in western Norway, known for flowing through a scenic fjord landscape.
-
A.
Tlass
Tlass is a Syrian family name most prominently associated with Mustafa Tlass, a long-serving defense minister under Hafez al-Assad.
-
B.
Thrylos
Thrylos is the popular nickname of Greek football club Olympiacos FC, reflecting its legendary status and storied success.
-
C.
Teurnia
Teurnia was an important ancient Roman city that served as a major administrative and cultural center in the province of Noricum, located in what is now southern Austria.
-
D.
Tarutyne
Tarutyne is an urban-type settlement in Odesa Oblast, southwestern Ukraine, serving as a local administrative and cultural center.
-
E.
Teisen
Teisen is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green spaces, and convenient access to public transportation.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e163a3c8190ab933411372c1573 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01f931408190828d87567cecaceb |
completed | May 9, 2026, 9:44 a.m. |
| NEDg | Description generation | batch_69ff034de0508190aea8068e9c3d04d3 |
completed | May 9, 2026, 9:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff03c0ebc081908b1a132256e9d004 |
completed | May 9, 2026, 9:52 a.m. |
Created at: April 10, 2026, 3:17 a.m.