Triple
T1517195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ostrava |
E32147
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object |
Lučina
Lučina is a river in the Moravian-Silesian Region of the Czech Republic that flows through the city of Ostrava.
|
E172957
|
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: Lučina | Statement: [Ostrava, locatedOnRiver, Lučina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lučina Context triple: [Ostrava, locatedOnRiver, Lučina]
-
A.
Jilava
Jilava is a locality in Romania best known for its historic prison and fortress, which were used for political detentions and executions, especially during the 20th century.
-
B.
Orava
Orava is a historical region in northern Slovakia and southern Poland, known for its mountainous landscapes, traditional villages, and the prominent Orava Castle.
-
C.
Brda
Brda is a river in northern Poland that flows through the Pomeranian region and is known for its scenic landscapes and popular kayaking routes.
-
D.
Pirna
Pirna is a historic town in eastern Germany situated on the River Elbe, known as a gateway to the Saxon Switzerland National Park.
-
E.
Morava
Morava is a Central European river that forms part of the border between Austria, the Czech Republic, and Slovakia before joining the Danube near Bratislava.
- 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: Lučina Triple: [Ostrava, locatedOnRiver, Lučina]
Generated description
Lučina is a river in the Moravian-Silesian Region of the Czech Republic that flows through the city of Ostrava.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lučina Target entity description: Lučina is a river in the Moravian-Silesian Region of the Czech Republic that flows through the city of Ostrava.
-
A.
Jilava
Jilava is a locality in Romania best known for its historic prison and fortress, which were used for political detentions and executions, especially during the 20th century.
-
B.
Orava
Orava is a historical region in northern Slovakia and southern Poland, known for its mountainous landscapes, traditional villages, and the prominent Orava Castle.
-
C.
Brda
Brda is a river in northern Poland that flows through the Pomeranian region and is known for its scenic landscapes and popular kayaking routes.
-
D.
Pirna
Pirna is a historic town in eastern Germany situated on the River Elbe, known as a gateway to the Saxon Switzerland National Park.
-
E.
Morava
Morava is a Central European river that forms part of the border between Austria, the Czech Republic, and Slovakia before joining the Danube near Bratislava.
- 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_69a885e8caf88190a5fbb6159ce87786 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a907eb7d108190bf26199744d510d7 |
completed | March 5, 2026, 4:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad2344f8d8819082e1ae5c980d0525 |
completed | March 8, 2026, 7:20 a.m. |
| NEDg | Description generation | batch_69ad23d86d088190bbea03d5d49bc009 |
completed | March 8, 2026, 7:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad2459c38c8190a8c166c2743a8936 |
completed | March 8, 2026, 7:25 a.m. |
Created at: March 4, 2026, 7:26 p.m.