Triple
T14723514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orne |
E345874
|
entity |
| Predicate | hasHistoricTown |
P847
|
FINISHED |
| Object |
Sées
Sées is a historic commune in northwestern France known for its impressive Gothic cathedral and role as a former episcopal seat in the Orne department.
|
E1127029
|
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: Sées | Statement: [Orne, hasHistoricTown, Sées]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sées Context triple: [Orne, hasHistoricTown, Sées]
-
A.
Bessin
Bessin is a historic coastal region in Normandy, northwestern France, known for its medieval heritage and its role in the D-Day landings of World War II.
-
B.
Bièvres
Bièvres is a commune in the Essonne department in the southern suburbs of Paris, France, known for its picturesque valley and proximity to the capital.
-
C.
Épron
Épron is a small commune in the Calvados department of the Normandy region in northwestern France.
-
D.
Frepillon
Frepillon is a small commune in the Val-d'Oise department in the Île-de-France region of northern France.
-
E.
Boucau
Boucau is a small commune in southwestern France’s Pyrénées-Atlantiques department, near the Atlantic coast and the city of Bayonne.
- 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: Sées Triple: [Orne, hasHistoricTown, Sées]
Generated description
Sées is a historic commune in northwestern France known for its impressive Gothic cathedral and role as a former episcopal seat in the Orne department.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sées Target entity description: Sées is a historic commune in northwestern France known for its impressive Gothic cathedral and role as a former episcopal seat in the Orne department.
-
A.
Bessin
Bessin is a historic coastal region in Normandy, northwestern France, known for its medieval heritage and its role in the D-Day landings of World War II.
-
B.
Bièvres
Bièvres is a commune in the Essonne department in the southern suburbs of Paris, France, known for its picturesque valley and proximity to the capital.
-
C.
Épron
Épron is a small commune in the Calvados department of the Normandy region in northwestern France.
-
D.
Frepillon
Frepillon is a small commune in the Val-d'Oise department in the Île-de-France region of northern France.
-
E.
Boucau
Boucau is a small commune in southwestern France’s Pyrénées-Atlantiques department, near the Atlantic coast and the city of Bayonne.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec25e9a14819081fa06fc601f295d |
completed | April 14, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72a181708190816c391f6a5d06f0 |
completed | May 8, 2026, 11:32 p.m. |
| NEDg | Description generation | batch_69fe773c861c81908ed25104c52336f1 |
completed | May 8, 2026, 11:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe77907f50819098ad0d1b5d7050ef |
completed | May 8, 2026, 11:53 p.m. |
Created at: April 10, 2026, 1:29 a.m.