Triple
T12845257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jelenia Góra |
E307156
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Erftstadt |
E623568
|
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: Erftstadt | Statement: [Jelenia Góra, twinTown, Erftstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erftstadt Context triple: [Jelenia Góra, twinTown, Erftstadt]
-
A.
Erftstadt
chosen
Erftstadt is a town in the Rhein-Erft district of North Rhine-Westphalia, Germany, located southwest of Cologne and known for its mix of historic villages and suburban residential areas.
-
B.
Schlettstadt
Schlettstadt, now known as Sélestat, is a historic town in the Alsace region of northeastern France noted for its medieval architecture and humanist heritage.
-
C.
Kleve
Kleve is a historic town in western Germany near the Dutch border, known for its medieval castle and role as the former capital of the Duchy of Cleves.
-
D.
Gescher
Gescher is a small town in western Germany’s Münsterland region, noted for its traditional bell foundries and rural character.
-
E.
Diemelstadt
Diemelstadt is a small town in the German state of North Rhine-Westphalia, known for its rural character and location near the Diemel River.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96ff3a7208190b93f6292ed5efc07 |
completed | April 10, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e70dc788190850278a40a5a62e4 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 9, 2026, 5:36 p.m.