Triple
T4235812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pamiers |
E94688
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object |
Crailsheim
Crailsheim is a town in the German state of Baden-Württemberg, known for its historical center and post-war reconstruction after heavy World War II damage.
|
E423694
|
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: Crailsheim | Statement: [Pamiers, twinTown, Crailsheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crailsheim Context triple: [Pamiers, twinTown, Crailsheim]
-
A.
Schelklingen
Schelklingen is a small historic town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its picturesque setting near the Swabian Jura.
-
B.
Brackenheim
Brackenheim is a small town in the German state of Baden-Württemberg, best known as the birthplace of Theodor Heuss, the first President of the Federal Republic of Germany.
-
C.
Rottweil
Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
-
D.
Lilienthal
Lilienthal is a German-origin surname borne by various notable individuals, including figures in aviation, science, and public service.
-
E.
Landsberg
Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
- 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: Crailsheim Triple: [Pamiers, twinTown, Crailsheim]
Generated description
Crailsheim is a town in the German state of Baden-Württemberg, known for its historical center and post-war reconstruction after heavy World War II damage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Crailsheim Target entity description: Crailsheim is a town in the German state of Baden-Württemberg, known for its historical center and post-war reconstruction after heavy World War II damage.
-
A.
Schelklingen
Schelklingen is a small historic town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its picturesque setting near the Swabian Jura.
-
B.
Brackenheim
Brackenheim is a small town in the German state of Baden-Württemberg, best known as the birthplace of Theodor Heuss, the first President of the Federal Republic of Germany.
-
C.
Rottweil
Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
-
D.
Lilienthal
Lilienthal is a German-origin surname borne by various notable individuals, including figures in aviation, science, and public service.
-
E.
Landsberg
Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
- 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_69b34537cc6481909cd0a96acbb33ef7 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e72ff588190a50c04ab975612dd |
completed | March 12, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a866c2448190aaed83d8da3669b8 |
completed | March 14, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69b5a8f374fc8190830286dfadc9bdbb |
completed | March 14, 2026, 6:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5a99a4a9c8190a7e9bbc119d8d775 |
completed | March 14, 2026, 6:31 p.m. |
Created at: March 12, 2026, 11:05 p.m.