Triple
T9505413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarthe |
E229255
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Mamers
Mamers is a small commune and town in the Sarthe department of northwestern France, known for its traditional markets and historic architecture.
|
E803258
|
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: Mamers | Statement: [Sarthe, contains, Mamers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mamers Context triple: [Sarthe, contains, Mamers]
-
A.
Duderstadt
Duderstadt is a historic small town in southern Lower Saxony, Germany, known for its well-preserved medieval timber-framed architecture and role as a regional center in the Eichsfeld area.
-
B.
Neustadt
Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
-
C.
Neustadt
Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
-
D.
Melle
Melle is a town in Lower Saxony, Germany, known for its rural character, historical architecture, and role as a regional economic center.
-
E.
Maschteich
Maschteich is an artificial pond in Hanover, Germany, situated in the Maschpark near the New Town Hall and known for its scenic urban green setting.
- 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: Mamers Triple: [Sarthe, contains, Mamers]
Generated description
Mamers is a small commune and town in the Sarthe department of northwestern France, known for its traditional markets and historic architecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mamers Target entity description: Mamers is a small commune and town in the Sarthe department of northwestern France, known for its traditional markets and historic architecture.
-
A.
Duderstadt
Duderstadt is a historic small town in southern Lower Saxony, Germany, known for its well-preserved medieval timber-framed architecture and role as a regional center in the Eichsfeld area.
-
B.
Neustadt
Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
-
C.
Neustadt
Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
-
D.
Melle
Melle is a town in Lower Saxony, Germany, known for its rural character, historical architecture, and role as a regional economic center.
-
E.
Maschteich
Maschteich is an artificial pond in Hanover, Germany, situated in the Maschpark near the New Town Hall and known for its scenic urban green setting.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9850fe6c8190a5a96cfae12562c6 |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a1de2d88190a6a10379d2297510 |
completed | April 4, 2026, 4:19 p.m. |
| NEDg | Description generation | batch_69d13ad61c6c8190baad9c4f166ca1ae |
completed | April 4, 2026, 4:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d13b4a7b808190badf83c88fb06b82 |
completed | April 4, 2026, 4:24 p.m. |
Created at: March 30, 2026, 7:57 p.m.