Triple
T11051719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salekhard |
E261270
|
entity |
| Predicate | originalName |
P65
|
FINISHED |
| Object |
Obdorsk
Obdorsk is the historical name of the Arctic city now known as Salekhard in northwestern Siberia, Russia.
|
E901404
|
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: Obdorsk | Statement: [Salekhard, originalName, Obdorsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Obdorsk Context triple: [Salekhard, originalName, Obdorsk]
-
A.
Makarska
Makarska is a coastal town and popular tourist resort on the Adriatic Sea in southern Croatia, known for its beaches and the nearby Biokovo mountain range.
-
B.
Primorsk
Primorsk is a port town in northwestern Russia situated on the coast of the Gulf of Finland in Leningrad Oblast.
-
C.
Dubrovno
Dubrovno is a small town in eastern Belarus, historically part of the Russian Empire and home to a significant Jewish community in the 19th and early 20th centuries.
-
D.
Dravograd
Dravograd is a small Slovenian town in the Carinthia region, known for its location at the confluence of the Drava and Meža rivers and its historical role as a regional center.
-
E.
Primorsko
Primorsko is a Bulgarian Black Sea coastal town and resort known for its beaches and tourism, located in southeastern Bulgaria.
- 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: Obdorsk Triple: [Salekhard, originalName, Obdorsk]
Generated description
Obdorsk is the historical name of the Arctic city now known as Salekhard in northwestern Siberia, Russia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Obdorsk Target entity description: Obdorsk is the historical name of the Arctic city now known as Salekhard in northwestern Siberia, Russia.
-
A.
Makarska
Makarska is a coastal town and popular tourist resort on the Adriatic Sea in southern Croatia, known for its beaches and the nearby Biokovo mountain range.
-
B.
Primorsk
Primorsk is a port town in northwestern Russia situated on the coast of the Gulf of Finland in Leningrad Oblast.
-
C.
Dubrovno
Dubrovno is a small town in eastern Belarus, historically part of the Russian Empire and home to a significant Jewish community in the 19th and early 20th centuries.
-
D.
Dravograd
Dravograd is a small Slovenian town in the Carinthia region, known for its location at the confluence of the Drava and Meža rivers and its historical role as a regional center.
-
E.
Primorsko
Primorsko is a Bulgarian Black Sea coastal town and resort known for its beaches and tourism, located in southeastern Bulgaria.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798698bd88190aa97afd37f55e19f |
completed | April 9, 2026, 12:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3aa146b148190a87205e542cc718f |
completed | April 18, 2026, 3:58 p.m. |
| NEDg | Description generation | batch_69e3ad0379888190b2f56d36d79bf97d |
completed | April 18, 2026, 4:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3b20f20bc8190a848c6fca8e2427f |
completed | April 18, 2026, 4:32 p.m. |
Created at: April 8, 2026, 9:26 p.m.