Triple
T11206558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marne-la-Vallée |
E265178
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Serris |
E268191
|
NE FINISHED |
How this triple was built (2 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: Serris | Statement: [Marne-la-Vallée, hasPart, Serris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serris Context triple: [Marne-la-Vallée, hasPart, Serris]
-
A.
Serris
chosen
Serris is a French suburban town in the Île-de-France region best known for hosting the Val d'Europe area adjacent to Disneyland Paris.
-
B.
Étampes
Étampes is a historic commune and former royal town in northern France, located in the Essonne department in the Île-de-France region.
-
C.
Sucy-en-Brie
Sucy-en-Brie is a suburban commune in the southeastern outskirts of Paris, France, known for its residential character and green spaces.
-
D.
Villiers-le-Sec
Villiers-le-Sec is a small French commune located in the Calvados department of the Normandy region in northwestern France.
-
E.
Mézidon Vallée d'Auge
Mézidon Vallée d'Auge is a commune in the Calvados department of northwestern France, known for its location in the historic Pays d'Auge region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d4eef88190a7f05bca82d919b9 |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd191f84bc819096d6cc6167732a98 |
completed | May 7, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:30 p.m.