Triple
T4103776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum Abteiberg |
E88400
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Mönchengladbach |
E382016
|
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: Mönchengladbach | Statement: [Museum Abteiberg, locatedIn, Mönchengladbach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mönchengladbach Context triple: [Museum Abteiberg, locatedIn, Mönchengladbach]
-
A.
Mönchengladbach
chosen
Mönchengladbach is a city in western Germany known for its textile industry heritage and its football club Borussia Mönchengladbach.
-
B.
Dortmund
Dortmund is a major city in western Germany known for its rich football culture, industrial heritage, and home club Borussia Dortmund.
-
C.
Krefeld
Krefeld is a city in western Germany near the Rhine River, known historically for its textile and silk industry.
-
D.
Gelsenkirchen
Gelsenkirchen is a city in western Germany known for its strong football culture and modern stadium, Veltins-Arena, home to FC Schalke 04.
-
E.
Bochum
Bochum is a major city in Germany’s Ruhr region known for its industrial heritage, cultural institutions, and large university.
- 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_69aed9484fb881909146f4c772ad277c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd116dac8190952cb2ddf63216ec |
completed | March 9, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b7a917c8190914a5ffe1297fdc8 |
completed | March 14, 2026, 2:06 p.m. |
Created at: March 9, 2026, 3:40 p.m.