Triple
T9495220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wagria |
E228986
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Ratekau
Ratekau is a municipality in the district of Ostholstein in Schleswig-Holstein, northern Germany, near the Baltic Sea coast.
|
E802830
|
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: Ratekau | Statement: [Wagria, contains, Ratekau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ratekau Context triple: [Wagria, contains, Ratekau]
-
A.
Temerloh
Temerloh is a town in central Pahang, Malaysia, known as a regional commercial hub and gateway to the state's interior.
-
B.
Kuala Kangsar
Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
-
C.
Kulim
Kulim is a prominent town and industrial hub in the Malaysian state of Kedah, known for its high-tech manufacturing and proximity to Penang.
-
D.
Kuantan
Kuantan is a coastal city on the east coast of Peninsular Malaysia known as a major economic and cultural center and gateway to the South China Sea.
-
E.
Kuala Pilah
Kuala Pilah is a historic inland town in the Malaysian state of Negeri Sembilan, known for its traditional Minangkabau cultural heritage and role as an administrative and commercial center for the surrounding rural district.
- 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: Ratekau Triple: [Wagria, contains, Ratekau]
Generated description
Ratekau is a municipality in the district of Ostholstein in Schleswig-Holstein, northern Germany, near the Baltic Sea coast.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ratekau Target entity description: Ratekau is a municipality in the district of Ostholstein in Schleswig-Holstein, northern Germany, near the Baltic Sea coast.
-
A.
Temerloh
Temerloh is a town in central Pahang, Malaysia, known as a regional commercial hub and gateway to the state's interior.
-
B.
Kuala Kangsar
Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
-
C.
Kulim
Kulim is a prominent town and industrial hub in the Malaysian state of Kedah, known for its high-tech manufacturing and proximity to Penang.
-
D.
Kuantan
Kuantan is a coastal city on the east coast of Peninsular Malaysia known as a major economic and cultural center and gateway to the South China Sea.
-
E.
Kuala Pilah
Kuala Pilah is a historic inland town in the Malaysian state of Negeri Sembilan, known for its traditional Minangkabau cultural heritage and role as an administrative and commercial center for the surrounding rural district.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95eb87b081908fc7255598cd9a24 |
completed | April 1, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12d34967881909980be6f1be80885 |
completed | April 4, 2026, 3:24 p.m. |
| NEDg | Description generation | batch_69d13113474881909201282ce1385073 |
completed | April 4, 2026, 3:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d131ade0588190bdf3cfdbbdd6df8e |
completed | April 4, 2026, 3:43 p.m. |
Created at: March 30, 2026, 7:56 p.m.