Triple
T13812267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ligne 2 |
E331921
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | La Chapelle |
E748930
|
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: La Chapelle | Statement: [Ligne 2, hasStation, La Chapelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Chapelle Context triple: [Ligne 2, hasStation, La Chapelle]
-
A.
La Chapelle
chosen
La Chapelle is a neighborhood in northern Paris known for its multicultural character, bustling streets, and proximity to major transport hubs like Gare du Nord.
-
B.
Châtel
Châtel is a French Alpine village and ski resort in the Haute-Savoie region, known for its traditional mountain charm and inclusion in the Portes du Soleil ski area.
-
C.
Assencières
Assencières is a small commune in the Aube department of north-central France.
-
D.
La Chapelle-des-Marais
La Chapelle-des-Marais is a commune in western France’s Loire-Atlantique department, known for its marshland landscapes and rural character.
-
E.
La Chapelle-d’Abondance
La Chapelle-d’Abondance is a French Alpine village and ski resort known for its mountain scenery, traditional Savoyard character, and access to the Portes du Soleil ski area.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de027198f8819095da3e714ac241f5 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb648146c8190842a3da4e4c0e217 |
completed | May 7, 2026, 3:56 p.m. |
Created at: April 9, 2026, 10:12 p.m.