Triple
T10136317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Saint-Omer |
E226863
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Longuenesse
Longuenesse is a commune in the Pas-de-Calais department in northern France, situated near the town of Saint-Omer.
|
E843301
|
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: Longuenesse | Statement: [Arrondissement of Saint-Omer, contains, Longuenesse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Longuenesse Context triple: [Arrondissement of Saint-Omer, contains, Longuenesse]
-
A.
Bouchet
Bouchet is a surname most notably associated with Edward Alexander Bouchet, one of the first African Americans to earn a Ph.D. in the United States.
-
B.
Merlav
Merlav is a small island and Oceanic language community in Vanuatu, known for its distinct Mwerlap language and culture.
-
C.
Souvestre
Souvestre is a French surname notably borne by educator Marie Souvestre, known for her progressive influence on women’s education in the 19th century.
-
D.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
-
E.
Baïse
Baïse is a river in southwestern France that flows through the Occitanie and Nouvelle-Aquitaine regions before joining the Garonne.
- 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: Longuenesse Triple: [Arrondissement of Saint-Omer, contains, Longuenesse]
Generated description
Longuenesse is a commune in the Pas-de-Calais department in northern France, situated near the town of Saint-Omer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Longuenesse Target entity description: Longuenesse is a commune in the Pas-de-Calais department in northern France, situated near the town of Saint-Omer.
-
A.
Bouchet
Bouchet is a surname most notably associated with Edward Alexander Bouchet, one of the first African Americans to earn a Ph.D. in the United States.
-
B.
Merlav
Merlav is a small island and Oceanic language community in Vanuatu, known for its distinct Mwerlap language and culture.
-
C.
Souvestre
Souvestre is a French surname notably borne by educator Marie Souvestre, known for her progressive influence on women’s education in the 19th century.
-
D.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
-
E.
Baïse
Baïse is a river in southwestern France that flows through the Occitanie and Nouvelle-Aquitaine regions before joining the Garonne.
- 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_69ca8433ec308190b8b25a6fe359c34c |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cde87fae288190bb4f13e1ae90f50a |
completed | April 2, 2026, 3:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e5e4664081908c1821006bd2f57f |
completed | April 5, 2026, 10:44 p.m. |
| NEDg | Description generation | batch_69d2e73e4d5081909f0068d3bed583d3 |
completed | April 5, 2026, 10:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d2e7eea4d88190a2ec6d22a83934b3 |
completed | April 5, 2026, 10:53 p.m. |
Created at: March 30, 2026, 9:06 p.m.