Triple
T9164269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weißenfels district |
E219906
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Tagewerben
Tagewerben is a small municipality in the Weißenfels area of Saxony-Anhalt in eastern Germany.
|
E782917
|
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: Tagewerben | Statement: [Weißenfels district, hasMunicipality, Tagewerben]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tagewerben Context triple: [Weißenfels district, hasMunicipality, Tagewerben]
-
A.
Tagaste
Tagaste was an ancient North African town in the Roman province of Numidia, best known as the birthplace of Saint Augustine and his mother Saint Monica.
-
B.
Tiendesitas
Tiendesitas is a popular shopping and lifestyle complex in Pasig, Metro Manila, known for its Filipino-themed architecture, handicrafts, food, and live entertainment.
-
C.
Ehlhalten
Ehlhalten is a village and district of the town of Eppstein in the Rheingau-Taunus region of Hesse, Germany.
-
D.
Kehrsatz
Kehrsatz is a municipality in the canton of Bern, Switzerland, situated just south of the city of Bern within its metropolitan region.
-
E.
Taznatit
Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
- 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: Tagewerben Triple: [Weißenfels district, hasMunicipality, Tagewerben]
Generated description
Tagewerben is a small municipality in the Weißenfels area of Saxony-Anhalt in eastern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tagewerben Target entity description: Tagewerben is a small municipality in the Weißenfels area of Saxony-Anhalt in eastern Germany.
-
A.
Tagaste
Tagaste was an ancient North African town in the Roman province of Numidia, best known as the birthplace of Saint Augustine and his mother Saint Monica.
-
B.
Tiendesitas
Tiendesitas is a popular shopping and lifestyle complex in Pasig, Metro Manila, known for its Filipino-themed architecture, handicrafts, food, and live entertainment.
-
C.
Ehlhalten
Ehlhalten is a village and district of the town of Eppstein in the Rheingau-Taunus region of Hesse, Germany.
-
D.
Kehrsatz
Kehrsatz is a municipality in the canton of Bern, Switzerland, situated just south of the city of Bern within its metropolitan region.
-
E.
Taznatit
Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
- 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_69ca83e3633c81908688a9fa2306ba99 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaa2ee64c8190a9a5abafe5d0b086 |
completed | April 1, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0547df750819095853f21cf740c63 |
completed | April 3, 2026, 11:59 p.m. |
| NEDg | Description generation | batch_69d0554fda40819083ef2d13d6fba905 |
completed | April 4, 2026, 12:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d055ca4fc08190b30e1b31ded51189 |
completed | April 4, 2026, 12:05 a.m. |
Created at: March 30, 2026, 7:21 p.m.