Triple
T2243193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bombing of Wieluń |
E49442
|
entity |
| Predicate | target |
P860
|
FINISHED |
| Object | Wieluń |
E246981
|
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: Wieluń | Statement: [Bombing of Wieluń, target, Wieluń]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wieluń Context triple: [Bombing of Wieluń, target, Wieluń]
-
A.
Wieluń
chosen
Wieluń is a town in south-central Poland historically known as one of the first targets of German aerial bombardment at the start of World War II.
-
B.
Muszyna
Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
-
C.
Mława
Mława is a town in north-central Poland known for its historical significance, including a major World War II battle, and its regional cultural and economic role.
-
D.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
E.
Oleśnica
Oleśnica is a historic town in southwestern Poland known for its Renaissance castle and well-preserved old town.
- 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0c157e88190a5bc876d9591a24b |
completed | March 7, 2026, 6:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71bfb47881908c93333a9e808420 |
completed | March 9, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:47 p.m.