Triple
T7843043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bellegarde-sur-Valserine |
E181849
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object | Tychy |
E526085
|
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: Tychy | Statement: [Bellegarde-sur-Valserine, twinnedWith, Tychy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tychy Context triple: [Bellegarde-sur-Valserine, twinnedWith, Tychy]
-
A.
Tychy
chosen
Tychy is a city in the Silesian region of southern Poland, known for its brewing industry and role as a planned industrial center.
-
B.
Kalisz
Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
-
C.
Chorzów
Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
-
D.
Tczew
Tczew is a historic town in northern Poland on the Vistula River, known for its important railway bridges and role as a regional transport hub.
-
E.
Kociewie
Kociewie is an ethnocultural region in northern Poland known for its distinct folk traditions, dialect, and rural landscapes.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb163b32688190b463a9cd8fa3c690 |
completed | March 31, 2026, 12:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4415b7f848190a9fc8b08824f0b9b |
completed | April 19, 2026, 2:43 a.m. |
Created at: March 30, 2026, 4:48 p.m.