Triple
T13414421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lanaudière |
E313172
|
entity |
| Predicate | hasAdministrativeCenter |
P1474
|
FINISHED |
| Object | Joliette |
E584420
|
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: Joliette | Statement: [Lanaudière, hasAdministrativeCenter, Joliette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joliette Context triple: [Lanaudière, hasAdministrativeCenter, Joliette]
-
A.
Joliette
Joliette is a Montreal Metro station on the Green Line serving the Mercier–Hochelaga-Maisonneuve borough in Montreal, Quebec, Canada.
-
B.
Joliette, Quebec
chosen
Joliette, Quebec is a small city in the Lanaudière region northeast of Montreal, known as a regional cultural and administrative center.
-
C.
Pierrefonds
Pierrefonds is a residential suburban area on the Island of Montreal in Quebec, Canada, known for its diverse population and proximity to the Rivière des Prairies.
-
D.
Pierrefonds
Pierrefonds is a commune in northern France best known for its impressive medieval-style Château de Pierrefonds and its picturesque setting in the forest of Compiègne.
-
E.
Saint-Hyacinthe
Saint-Hyacinthe is a city in southwestern Quebec, Canada, known as an important regional center for agriculture, agri-food industries, and education.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb556948190af008c88e5bbf051 |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8c288c08190af46fe7d114df338 |
completed | May 3, 2026, 9:06 p.m. |
Created at: April 9, 2026, 9:39 p.m.