Triple
T10149630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lądek-Zdrój |
E232595
|
entity |
| Predicate | hasFormerName |
P65
|
FINISHED |
| Object |
Bad Landeck
Bad Landeck is the former German name for the spa town now known as Lądek-Zdrój in southwestern Poland.
|
E843425
|
NE FINISHED |
How this triple was built (4 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: Bad Landeck | Statement: [Lądek-Zdrój, hasFormerName, Bad Landeck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Landeck Context triple: [Lądek-Zdrój, hasFormerName, Bad Landeck]
-
A.
Bad Wildungen
Bad Wildungen is a German spa town in the state of Hesse, known for its mineral springs, health resorts, and extensive parklands.
-
B.
Wildenberg
Wildenberg is a small municipality in the Kelheim district of Lower Bavaria, Germany, known for its rural character and agricultural surroundings.
-
C.
Bad Elster
Bad Elster is a historic spa town in Saxony, Germany, renowned for its mineral springs and role as a traditional health resort.
-
D.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
E.
Bad Eilsen
Bad Eilsen is a spa town in Lower Saxony, Germany, historically notable for serving as the post–World War II headquarters of the Royal Air Force’s British Air Forces of Occupation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bad Landeck Triple: [Lądek-Zdrój, hasFormerName, Bad Landeck]
Generated description
Bad Landeck is the former German name for the spa town now known as Lądek-Zdrój in southwestern Poland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bad Landeck Target entity description: Bad Landeck is the former German name for the spa town now known as Lądek-Zdrój in southwestern Poland.
-
A.
Bad Wildungen
Bad Wildungen is a German spa town in the state of Hesse, known for its mineral springs, health resorts, and extensive parklands.
-
B.
Wildenberg
Wildenberg is a small municipality in the Kelheim district of Lower Bavaria, Germany, known for its rural character and agricultural surroundings.
-
C.
Bad Elster
Bad Elster is a historic spa town in Saxony, Germany, renowned for its mineral springs and role as a traditional health resort.
-
D.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
E.
Bad Eilsen
Bad Eilsen is a spa town in Lower Saxony, Germany, historically notable for serving as the post–World War II headquarters of the Royal Air Force’s British Air Forces of Occupation.
- F. None of above. chosen
Provenance (5 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_69ca84885e48819088a31b127cf44904 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec03e80c81909c813dae91c56272 |
completed | April 2, 2026, 4:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e6369c848190984394eedf2f07eb |
completed | April 5, 2026, 10:46 p.m. |
| NEDg | Description generation | batch_69d2e7408e58819083c43e334a87a09f |
completed | April 5, 2026, 10:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d2e7b854d08190ac2af642970b7f09 |
completed | April 5, 2026, 10:52 p.m. |
Created at: March 30, 2026, 9:08 p.m.