Triple
T13900266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dingolfing |
E334197
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Brumath
Brumath is a small commune in northeastern France’s Grand Est region, known for its historical roots dating back to Roman times.
|
E1098613
|
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: Brumath | Statement: [Dingolfing, hasTwinTown, Brumath]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brumath Context triple: [Dingolfing, hasTwinTown, Brumath]
-
A.
Haguenau
Haguenau is a historic town in northeastern France’s Alsace region, known for its medieval heritage, cultural traditions, and role as a local economic center.
-
B.
Willanzheim
Willanzheim is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and Franconian wine-growing tradition.
-
C.
Thionville
Thionville is a town in northeastern France near the Luxembourg border, known historically as a strategic industrial and military center in the Moselle region.
-
D.
Sarreguemines
Sarreguemines is a town in northeastern France near the German border, historically known for its ceramics and faience production.
-
E.
Lothier
Lothier was a medieval duchy in the Low Countries, historically associated with the Duchy of Brabant and forming part of the Holy Roman Empire.
- 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: Brumath Triple: [Dingolfing, hasTwinTown, Brumath]
Generated description
Brumath is a small commune in northeastern France’s Grand Est region, known for its historical roots dating back to Roman times.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brumath Target entity description: Brumath is a small commune in northeastern France’s Grand Est region, known for its historical roots dating back to Roman times.
-
A.
Haguenau
Haguenau is a historic town in northeastern France’s Alsace region, known for its medieval heritage, cultural traditions, and role as a local economic center.
-
B.
Willanzheim
Willanzheim is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and Franconian wine-growing tradition.
-
C.
Thionville
Thionville is a town in northeastern France near the Luxembourg border, known historically as a strategic industrial and military center in the Moselle region.
-
D.
Sarreguemines
Sarreguemines is a town in northeastern France near the German border, historically known for its ceramics and faience production.
-
E.
Lothier
Lothier was a medieval duchy in the Low Countries, historically associated with the Duchy of Brabant and forming part of the Holy Roman Empire.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25d8897881908b770cdb565898d4 |
completed | April 14, 2026, 11:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bb05bb481909a0ad528e998fdf1 |
completed | May 8, 2026, 3:42 a.m. |
| NEDg | Description generation | batch_69fd5d078b8081908810acb77be74b2b |
completed | May 8, 2026, 3:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5d7e07a08190be5154674f7478fb |
completed | May 8, 2026, 3:50 a.m. |
Created at: April 9, 2026, 10:15 p.m.