Triple
T1346084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daugava River |
E28573
|
entity |
| Predicate | crossesCity |
P13729
|
FINISHED |
| Object |
Jekabpils
Jekabpils is a town in southeastern Latvia known for its historic architecture and scenic location along the Daugava River.
|
E157505
|
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: Jekabpils | Statement: [Daugava River, crossesCity, Jekabpils]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jekabpils Context triple: [Daugava River, crossesCity, Jekabpils]
-
A.
Jelgava
Jelgava is a city in central Latvia known for its historic Jelgava Palace and role as a regional cultural and educational center.
-
B.
Daugavpils
Daugavpils is Latvia’s second-largest city, known as the birthplace of abstract expressionist painter Mark Rothko and for its multicultural heritage and 19th-century fortress.
-
C.
Ventspils
Ventspils is a port city on Latvia’s Baltic Sea coast known for its major ice-free harbor, oil and cargo terminals, and well-preserved historic center.
-
D.
Viedma
Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
-
E.
Liepāja, Latvia
Liepāja is a major port city on Latvia’s Baltic Sea coast, known for its historic architecture, naval heritage, and cultural life.
- 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: Jekabpils Triple: [Daugava River, crossesCity, Jekabpils]
Generated description
Jekabpils is a town in southeastern Latvia known for its historic architecture and scenic location along the Daugava River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jekabpils Target entity description: Jekabpils is a town in southeastern Latvia known for its historic architecture and scenic location along the Daugava River.
-
A.
Jelgava
Jelgava is a city in central Latvia known for its historic Jelgava Palace and role as a regional cultural and educational center.
-
B.
Daugavpils
Daugavpils is Latvia’s second-largest city, known as the birthplace of abstract expressionist painter Mark Rothko and for its multicultural heritage and 19th-century fortress.
-
C.
Ventspils
Ventspils is a port city on Latvia’s Baltic Sea coast known for its major ice-free harbor, oil and cargo terminals, and well-preserved historic center.
-
D.
Viedma
Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
-
E.
Liepāja, Latvia
Liepāja is a major port city on Latvia’s Baltic Sea coast, known for its historic architecture, naval heritage, and cultural life.
- 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c23e84188190b0395c57dd45b62a |
completed | March 1, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acd47917d88190a13d7705f09c0b58 |
completed | March 8, 2026, 1:44 a.m. |
| NEDg | Description generation | batch_69acd5314ac08190abf0ed287689dc5f |
completed | March 8, 2026, 1:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acd59842f08190976724ad981de3d8 |
completed | March 8, 2026, 1:49 a.m. |
Created at: March 1, 2026, 7:56 p.m.