Triple
T20826842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County of Moers |
E512724
|
entity |
| Predicate | sovereign |
P403
|
FINISHED |
| Object |
Counts of Moers
The Counts of Moers were a noble dynasty that ruled the small Lower Rhine territory of Moers in what is now western Germany during the Middle Ages and early modern period.
|
E1452425
|
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: Counts of Moers | Statement: [County of Moers, sovereign, Counts of Moers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Counts of Moers Context triple: [County of Moers, sovereign, Counts of Moers]
-
A.
MÖR
MÖR is the station code for Mörby centrum, a metro station on the Stockholm Metro system in Sweden.
-
B.
Mohrungen
Mohrungen is a historic town in former East Prussia (now Morąg in northern Poland), known as the birthplace of philosopher and theologian Johann Gottfried Herder.
-
C.
Mössinger
Mössinger is a German surname most notably borne by Ingrid Mössinger, a prominent figure in the German art and museum world.
-
D.
Moser
Moser is a Norwegian surname most prominently associated with Nobel Prize–winning neuroscientists May-Britt and Edvard Moser.
-
E.
Munsbach
Munsbach is a small village in central Luxembourg, known for its rural setting and proximity to the capital city.
- 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: Counts of Moers Triple: [County of Moers, sovereign, Counts of Moers]
Generated description
The Counts of Moers were a noble dynasty that ruled the small Lower Rhine territory of Moers in what is now western Germany during the Middle Ages and early modern period.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Counts of Moers Target entity description: The Counts of Moers were a noble dynasty that ruled the small Lower Rhine territory of Moers in what is now western Germany during the Middle Ages and early modern period.
-
A.
MÖR
MÖR is the station code for Mörby centrum, a metro station on the Stockholm Metro system in Sweden.
-
B.
Mohrungen
Mohrungen is a historic town in former East Prussia (now Morąg in northern Poland), known as the birthplace of philosopher and theologian Johann Gottfried Herder.
-
C.
Mössinger
Mössinger is a German surname most notably borne by Ingrid Mössinger, a prominent figure in the German art and museum world.
-
D.
Moser
Moser is a Norwegian surname most prominently associated with Nobel Prize–winning neuroscientists May-Britt and Edvard Moser.
-
E.
Munsbach
Munsbach is a small village in central Luxembourg, known for its rural setting and proximity to the capital city.
- 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2fe54608190a061274bf4316610 |
completed | April 21, 2026, 12:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09007dd6a08190a00a462f9aecfc48 |
completed | May 16, 2026, 11:40 p.m. |
| NEDg | Description generation | batch_6a0901bb9cf481908e9b631477b1c16d |
completed | May 16, 2026, 11:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09023cf27081908eb246367215ae12 |
completed | May 16, 2026, 11:48 p.m. |
Created at: April 16, 2026, 12:41 p.m.