Triple
T16019598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cergy-Pontoise urban area |
E388564
|
entity |
| Predicate | containsCommune |
P15149
|
FINISHED |
| Object | Pontoise |
E70703
|
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: Pontoise | Statement: [Cergy-Pontoise urban area, containsCommune, Pontoise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pontoise Context triple: [Cergy-Pontoise urban area, containsCommune, Pontoise]
-
A.
Pontoise
chosen
Pontoise is a historic commune in the northwestern suburbs of Paris, France, known for its picturesque setting on the River Oise and its association with Impressionist painters.
-
B.
Crépy-en-Valois
Crépy-en-Valois is a commune in the Oise department of northern France, known for its historic medieval center and role as a regional rail terminus.
-
C.
Pontois
Pontois is the French demonym referring to inhabitants of the commune of Pont-de-l’Isère in southeastern France.
-
D.
Armentières
Armentières is a commune in northern France near the Belgian border, historically known for its textile industry and World War I significance.
-
E.
Bazeilles
Bazeilles is a commune in northeastern France, historically notable as a battlefield during the Franco-Prussian War.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183222e4c81909a3ab51446b671bd |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbcdf2548190999a6d093c7fb64a |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 4:55 a.m.