Triple
T4367683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bourg-en-Bresse |
E98816
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Brzeg |
E412025
|
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: Brzeg | Statement: [Bourg-en-Bresse, hasTwinTown, Brzeg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brzeg Context triple: [Bourg-en-Bresse, hasTwinTown, Brzeg]
-
A.
Brzeg
chosen
Brzeg is a historic town in southwestern Poland known for its Renaissance castle and well-preserved old town.
-
B.
Ustka
Ustka is a Baltic Sea coastal town in northern Poland known as a popular seaside resort and fishing port.
-
C.
Olsztynek
Olsztynek is a small historic town in northern Poland known for its open-air ethnographic museum and location within the picturesque Warmian-Masurian lake district.
-
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.
Kwidzyn
Kwidzyn is a historic town in northern Poland known for its medieval Teutonic castle complex and Gothic cathedral.
- 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_69b3454db3708190aeafd814413c4c3d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35201be7081908808e81634060f95 |
completed | March 12, 2026, 11:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5187dfe008190ac60e042527e55b3 |
completed | March 26, 2026, 11:29 a.m. |
Created at: March 12, 2026, 11:17 p.m.