Triple
T15619566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrągowo |
E375511
|
entity |
| Predicate | historicalName |
P65
|
FINISHED |
| Object |
Sensburg
Sensburg is the former German name of the town now known as Mrągowo in northeastern Poland, historically part of East Prussia.
|
E1168643
|
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: Sensburg | Statement: [Mrągowo, historicalName, Sensburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sensburg Context triple: [Mrągowo, historicalName, Sensburg]
-
A.
Kingsburg
Kingsburg is a small, historically Swedish-themed city in California’s San Joaquin Valley known for its agricultural community and distinctive Scandinavian character.
-
B.
Elmora
Elmora is a residential neighborhood within the city of Elizabeth in Union County, New Jersey.
-
C.
Hofstadt
Hofstadt is the maiden surname of Betty Draper, a central character on the television series "Mad Men."
-
D.
Keenesburg
Keenesburg is a small town in northeastern Colorado known for its rural character and proximity to the Denver metropolitan area.
-
E.
Brydekirk
Brydekirk is a small village in Dumfries and Galloway in southwest Scotland, known for its rural setting and proximity to the River Annan.
- 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: Sensburg Triple: [Mrągowo, historicalName, Sensburg]
Generated description
Sensburg is the former German name of the town now known as Mrągowo in northeastern Poland, historically part of East Prussia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sensburg Target entity description: Sensburg is the former German name of the town now known as Mrągowo in northeastern Poland, historically part of East Prussia.
-
A.
Kingsburg
Kingsburg is a small, historically Swedish-themed city in California’s San Joaquin Valley known for its agricultural community and distinctive Scandinavian character.
-
B.
Elmora
Elmora is a residential neighborhood within the city of Elizabeth in Union County, New Jersey.
-
C.
Hofstadt
Hofstadt is the maiden surname of Betty Draper, a central character on the television series "Mad Men."
-
D.
Keenesburg
Keenesburg is a small town in northeastern Colorado known for its rural character and proximity to the Denver metropolitan area.
-
E.
Brydekirk
Brydekirk is a small village in Dumfries and Galloway in southwest Scotland, known for its rural setting and proximity to the River Annan.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e997ce481909b2f10d25705fbc6 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f3b643c819093230df6cfe440b9 |
completed | May 9, 2026, 4:22 p.m. |
| NEDg | Description generation | batch_69ff5fea7cb48190a1acb9201a12fa32 |
completed | May 9, 2026, 4:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff62e84bec81908a4885bf7f8f3749 |
completed | May 9, 2026, 4:38 p.m. |
Created at: April 10, 2026, 4:13 a.m.