Triple
T7091518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canton of Courseulles-sur-Mer |
E165204
|
entity |
| Predicate | containsAdministrativeTerritorialEntity |
P747
|
FINISHED |
| Object |
Amblie
Amblie is a small commune in the Calvados department of the Normandy region in northwestern France.
|
E640664
|
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: Amblie | Statement: [Canton of Courseulles-sur-Mer, containsAdministrativeTerritorialEntity, Amblie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amblie Context triple: [Canton of Courseulles-sur-Mer, containsAdministrativeTerritorialEntity, Amblie]
-
A.
Tamina
The Tamina is a river in eastern Switzerland known for flowing through the deep Tamina Gorge before joining the Alpine Rhine.
-
B.
Lasky
Lasky is a surname most notably associated with Jesse L. Lasky, a pioneering American film producer and co-founder of Paramount Pictures.
-
C.
Angourie
Angourie is a small coastal village in New South Wales, Australia, renowned for its surf breaks and scenic beaches.
-
D.
Tully
Tully is a 2018 comedy-drama film starring Charlize Theron as an overwhelmed mother who forms an unexpected bond with her night nanny.
-
E.
Tully
Tully is a surname most notably associated with Brent Tully, an astronomer known for his work on the large-scale structure of the universe and galaxy distributions.
- 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: Amblie Triple: [Canton of Courseulles-sur-Mer, containsAdministrativeTerritorialEntity, Amblie]
Generated description
Amblie is a small commune in the Calvados department of the Normandy region in northwestern France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Amblie Target entity description: Amblie is a small commune in the Calvados department of the Normandy region in northwestern France.
-
A.
Tamina
The Tamina is a river in eastern Switzerland known for flowing through the deep Tamina Gorge before joining the Alpine Rhine.
-
B.
Lasky
Lasky is a surname most notably associated with Jesse L. Lasky, a pioneering American film producer and co-founder of Paramount Pictures.
-
C.
Angourie
Angourie is a small coastal village in New South Wales, Australia, renowned for its surf breaks and scenic beaches.
-
D.
Tully
Tully is a 2018 comedy-drama film starring Charlize Theron as an overwhelmed mother who forms an unexpected bond with her night nanny.
-
E.
Tully
Tully is a surname most notably associated with Brent Tully, an astronomer known for his work on the large-scale structure of the universe and galaxy distributions.
- 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_69c6887e8c10819091cee237560d32da |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e53132288190b6da361d9c7218ab |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7948cb3d48190993134d709924e3d |
completed | March 28, 2026, 8:42 a.m. |
| NEDg | Description generation | batch_69c7962ec0bc8190a9223ebb245d0914 |
completed | March 28, 2026, 8:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c79709ed808190a9f09f5350ba2ffd |
completed | March 28, 2026, 8:53 a.m. |
Created at: March 27, 2026, 2:41 p.m.