Triple
T17699863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joliette station |
E441267
|
entity |
| Predicate | adjacentStation |
P5707
|
FINISHED |
| Object |
Préfontaine station
Préfontaine station is a Montreal Metro station on the Green Line serving the Hochelaga-Maisonneuve area of Montreal, Quebec, Canada.
|
E1285086
|
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: Préfontaine station | Statement: [Joliette station, adjacentStation, Préfontaine station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Préfontaine station Context triple: [Joliette station, adjacentStation, Préfontaine station]
-
A.
Parc station
Parc station is a metro stop on the Charleroi Metro network in Charleroi, Belgium.
-
B.
Parc station
Parc station is a Montreal Metro station in the Parc-Extension area that serves the Blue Line and connects with commuter rail services.
-
C.
Nice-Ville station
Nice-Ville station is the main railway station in Nice, France, serving as a major hub for regional and long-distance train services along the French Riviera.
-
D.
Mabillon station
Mabillon station is a Paris Métro station in the 6th arrondissement, serving the Saint-Germain-des-Prés area on the Left Bank.
-
E.
Vaucelles station
Vaucelles station is a railway station serving the commune of Taverny in the northern suburbs of Paris, 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: Préfontaine station Triple: [Joliette station, adjacentStation, Préfontaine station]
Generated description
Préfontaine station is a Montreal Metro station on the Green Line serving the Hochelaga-Maisonneuve area of Montreal, Quebec, Canada.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Préfontaine station Target entity description: Préfontaine station is a Montreal Metro station on the Green Line serving the Hochelaga-Maisonneuve area of Montreal, Quebec, Canada.
-
A.
Parc station
Parc station is a Montreal Metro station in the Parc-Extension area that serves the Blue Line and connects with commuter rail services.
-
B.
Parc station
Parc station is a metro stop on the Charleroi Metro network in Charleroi, Belgium.
-
C.
Nice-Ville station
Nice-Ville station is the main railway station in Nice, France, serving as a major hub for regional and long-distance train services along the French Riviera.
-
D.
Mabillon station
Mabillon station is a Paris Métro station in the 6th arrondissement, serving the Saint-Germain-des-Prés area on the Left Bank.
-
E.
Vaucelles station
Vaucelles station is a railway station serving the commune of Taverny in the northern suburbs of Paris, 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e471597d5c8190bd06337239739cd7 |
completed | April 19, 2026, 6:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0242ec0b708190add75f3bd08fc446 |
completed | May 11, 2026, 8:58 p.m. |
| NEDg | Description generation | batch_6a024489b2ac81908741844724d4bdf3 |
completed | May 11, 2026, 9:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0244f947f48190ada0b4786926ff52 |
completed | May 11, 2026, 9:07 p.m. |
Created at: April 10, 2026, 10:04 a.m.