Triple
T11885852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Innviertel |
E282778
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Andorf
Andorf is a market town in the Innviertel region of Upper Austria, known for its rural character and local agricultural economy.
|
E952055
|
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: Andorf | Statement: [Innviertel, contains, Andorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andorf Context triple: [Innviertel, contains, Andorf]
-
A.
Eitorf
Eitorf is a municipality in western Germany situated along the River Sieg in the state of North Rhine-Westphalia.
-
B.
Mechernich
Mechernich is a small town in the Eifel region of North Rhine-Westphalia, Germany, known for its rural landscape and cultural landmarks such as the Bruder Klaus Field Chapel.
-
C.
Duisdorf
Duisdorf is a district of Bonn, Germany, known as a residential area with local commerce and public services within the borough of Hardtberg.
-
D.
Arnsberg
Arnsberg is a historic town in the Sauerland region of North Rhine-Westphalia, Germany, known for its medieval old town and surrounding forested hills.
-
E.
Andernach
Andernach is a historic German town on the Rhine River in Rhineland-Palatinate, known for its medieval architecture and one of the world’s highest cold-water geysers.
- 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: Andorf Triple: [Innviertel, contains, Andorf]
Generated description
Andorf is a market town in the Innviertel region of Upper Austria, known for its rural character and local agricultural economy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andorf Target entity description: Andorf is a market town in the Innviertel region of Upper Austria, known for its rural character and local agricultural economy.
-
A.
Eitorf
Eitorf is a municipality in western Germany situated along the River Sieg in the state of North Rhine-Westphalia.
-
B.
Mechernich
Mechernich is a small town in the Eifel region of North Rhine-Westphalia, Germany, known for its rural landscape and cultural landmarks such as the Bruder Klaus Field Chapel.
-
C.
Duisdorf
Duisdorf is a district of Bonn, Germany, known as a residential area with local commerce and public services within the borough of Hardtberg.
-
D.
Arnsberg
Arnsberg is a historic town in the Sauerland region of North Rhine-Westphalia, Germany, known for its medieval old town and surrounding forested hills.
-
E.
Andernach
Andernach is a historic German town on the Rhine River in Rhineland-Palatinate, known for its medieval architecture and one of the world’s highest cold-water geysers.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a13370819086386fecb99e4f0b |
completed | April 10, 2026, 10:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f281f488a8819082f40dfdd12f29a2 |
completed | April 29, 2026, 10:11 p.m. |
| NEDg | Description generation | batch_69f2d6da770481908cd8787ba6b5763b |
completed | April 30, 2026, 4:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f2dc57c3888190920b4275ed0b5bff |
completed | April 30, 2026, 4:36 a.m. |
Created at: April 8, 2026, 9:44 p.m.