Triple
T18134029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Muret |
E434089
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Seysses
Seysses is a commune in southwestern France, located in the Haute-Garonne department near Toulouse.
|
E1312334
|
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: Seysses | Statement: [Arrondissement of Muret, contains, Seysses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seysses Context triple: [Arrondissement of Muret, contains, Seysses]
-
A.
Cuers
Cuers is a commune in the Var department of southeastern France, situated inland from Toulon in the Provence-Alpes-Côte d’Azur region.
-
B.
Bonnieux
Bonnieux is a picturesque hilltop village in southeastern France’s Provence region, known for its historic stone houses, terraced streets, and panoramic views over the Luberon valley.
-
C.
Marignane
Marignane is a commune in southern France near Marseille, known for hosting Marseille Provence Airport and its proximity to the Mediterranean coast.
-
D.
Vert-le-Grand
Vert-le-Grand is a small commune in the Essonne department in the Île-de-France region of northern France.
-
E.
Saint-Florent
Saint-Florent is a picturesque coastal commune and popular yachting and beach resort on the northern coast of Corsica, France.
- 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: Seysses Triple: [Arrondissement of Muret, contains, Seysses]
Generated description
Seysses is a commune in southwestern France, located in the Haute-Garonne department near Toulouse.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seysses Target entity description: Seysses is a commune in southwestern France, located in the Haute-Garonne department near Toulouse.
-
A.
Cuers
Cuers is a commune in the Var department of southeastern France, situated inland from Toulon in the Provence-Alpes-Côte d’Azur region.
-
B.
Bonnieux
Bonnieux is a picturesque hilltop village in southeastern France’s Provence region, known for its historic stone houses, terraced streets, and panoramic views over the Luberon valley.
-
C.
Marignane
Marignane is a commune in southern France near Marseille, known for hosting Marseille Provence Airport and its proximity to the Mediterranean coast.
-
D.
Vert-le-Grand
Vert-le-Grand is a small commune in the Essonne department in the Île-de-France region of northern France.
-
E.
Saint-Florent
Saint-Florent is a picturesque coastal commune and popular yachting and beach resort on the northern coast of Corsica, France.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de055c608190a090c2737904e5f9 |
completed | April 19, 2026, 1:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a039effedd88190b7398132f15c5265 |
completed | May 12, 2026, 9:43 p.m. |
| NEDg | Description generation | batch_6a039fdd9c4c819083b450657d0ece43 |
completed | May 12, 2026, 9:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03a0d6de8c8190b1f94c7de0856143 |
completed | May 12, 2026, 9:51 p.m. |
Created at: April 10, 2026, 10:29 a.m.