Triple
T9938382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Illkirch-Graffenstaden |
E194012
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Leingarten
Leingarten is a municipality in the Heilbronn district of Baden-Württemberg, Germany, known for its wine-growing tradition and location near the city of Heilbronn.
|
E830942
|
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: Leingarten | Statement: [Illkirch-Graffenstaden, hasTwinTown, Leingarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leingarten Context triple: [Illkirch-Graffenstaden, hasTwinTown, Leingarten]
-
A.
Riedergarten
Riedergarten is a historic public garden and popular green oasis located in the Bavarian city of Rosenheim, Germany.
-
B.
Gardingen
Gardingen is a small locality in northern Germany best known as the birthplace of the renowned classical scholar and historian Theodor Mommsen.
-
C.
Steingaden
Steingaden is a Bavarian municipality in southern Germany known for its picturesque alpine setting and proximity to the UNESCO-listed Wies Church.
-
D.
Lustgarten
Lustgarten is a historic public park and square on Berlin’s Museum Island, long used as a parade ground and gathering place.
-
E.
Heiderhof
Heiderhof is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
- 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: Leingarten Triple: [Illkirch-Graffenstaden, hasTwinTown, Leingarten]
Generated description
Leingarten is a municipality in the Heilbronn district of Baden-Württemberg, Germany, known for its wine-growing tradition and location near the city of Heilbronn.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Leingarten Target entity description: Leingarten is a municipality in the Heilbronn district of Baden-Württemberg, Germany, known for its wine-growing tradition and location near the city of Heilbronn.
-
A.
Riedergarten
Riedergarten is a historic public garden and popular green oasis located in the Bavarian city of Rosenheim, Germany.
-
B.
Gardingen
Gardingen is a small locality in northern Germany best known as the birthplace of the renowned classical scholar and historian Theodor Mommsen.
-
C.
Steingaden
Steingaden is a Bavarian municipality in southern Germany known for its picturesque alpine setting and proximity to the UNESCO-listed Wies Church.
-
D.
Lustgarten
Lustgarten is a historic public park and square on Berlin’s Museum Island, long used as a parade ground and gathering place.
-
E.
Heiderhof
Heiderhof is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e64760819094f599f158d32f33 |
completed | April 2, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d228f259b081909ce8a90ec1adad0d |
completed | April 5, 2026, 9:18 a.m. |
| NEDg | Description generation | batch_69d22a78819481908ccff34730464f19 |
completed | April 5, 2026, 9:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d22b0fea588190a4928c361c2367ca |
completed | April 5, 2026, 9:27 a.m. |
Created at: March 30, 2026, 8:44 p.m.