Triple
T10449765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lusatian Neisse |
E246387
|
entity |
| Predicate | majorCityOnRiver |
P316
|
FINISHED |
| Object | Gubin |
E609853
|
NE FINISHED |
How this triple was built (2 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: Gubin | Statement: [Lusatian Neisse, majorCityOnRiver, Gubin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gubin Context triple: [Lusatian Neisse, majorCityOnRiver, Gubin]
-
A.
Gubin
chosen
Gubin is a town in western Poland situated on the Lusatian Neisse River, directly opposite the German town of Guben, forming a cross-border urban area.
-
B.
Gubakha
Gubakha is a small industrial town in Russia’s Perm Krai, historically associated with coal mining and chemical production in the Ural region.
-
C.
Gongjin
Gongjin is the courtesy name of Zhou Yu, a renowned Eastern Han dynasty military general and strategist best known for his role in the Battle of Red Cliffs.
-
D.
Gubongsan
Gubongsan is a mountain located in or near the city of Daejeon in South Korea, known for its hiking trails and scenic views.
-
E.
Kwangde
Kwangde is a prominent Himalayan mountain massif in Nepal’s Khumbu region, known for its steep faces and challenging climbing routes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe09af04819083db42f4de4cb0a9 |
completed | April 7, 2026, 12:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87efedf6c8190aa4b7bbe5f160eeb |
completed | April 10, 2026, 4:39 a.m. |
Created at: April 6, 2026, 12:17 p.m.