Triple
T11895556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunajská Streda |
E283026
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Senta |
E138568
|
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: Senta | Statement: [Dunajská Streda, hasTwinTown, Senta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Senta Context triple: [Dunajská Streda, hasTwinTown, Senta]
-
A.
Senta
Senta is the devoted young woman in Richard Wagner’s opera "Der fliegende Holländer" whose obsessive compassion and self-sacrificial love offer redemption to the cursed Dutchman.
-
B.
Senta
chosen
Senta is a town in northern Serbia, on the Tisa River, historically notable as the site of the 1697 Battle of Zenta between the Habsburg and Ottoman Empires.
-
C.
Anja
Anja is a feminine given name commonly used in various European countries, often considered a variant of Anna.
-
D.
Sanna
Sanna is a river in the Tyrol region of western Austria, known as a tributary of the Inn and a popular destination for whitewater sports.
-
E.
Jolanda
Jolanda is a feminine given name, commonly considered a variant of Yolanda, used in various European countries.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd1286808190949719f54ff49a01 |
completed | April 10, 2026, 11:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f41811e5ac8190a3e397e31f19bca1 |
completed | May 1, 2026, 3:03 a.m. |
Created at: April 8, 2026, 9:44 p.m.