Triple
T12132230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 5 (Brussels Metro) |
E288960
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Bizet station
Bizet station is a Brussels Metro station in the municipality of Anderlecht, serving passengers on the city’s Line 5.
|
E973840
|
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: Bizet station | Statement: [Line 5 (Brussels Metro), hasStation, Bizet station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bizet station Context triple: [Line 5 (Brussels Metro), hasStation, Bizet station]
-
A.
Mirabeau station
Mirabeau station is a Paris Métro station in the 16th arrondissement, notable for its single-direction platform layout and proximity to the Pont Mirabeau over the Seine.
-
B.
Malesherbes station
Malesherbes station is a railway station in France serving the town of Malesherbes and connecting it to the regional rail network.
-
C.
Malesherbes station
Malesherbes station is a Paris Métro station serving the 8th and 17th arrondissements of Paris on Line 3.
-
D.
Fabre station
Fabre station is a Montreal Metro station on the Blue Line serving the Rosemont–La Petite-Patrie borough.
-
E.
Beaurepaire station
Beaurepaire station is a commuter rail station serving the Beaurepaire area of Beaconsfield, a suburb on the Island of Montreal in Quebec, Canada.
- 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: Bizet station Triple: [Line 5 (Brussels Metro), hasStation, Bizet station]
Generated description
Bizet station is a Brussels Metro station in the municipality of Anderlecht, serving passengers on the city’s Line 5.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bizet station Target entity description: Bizet station is a Brussels Metro station in the municipality of Anderlecht, serving passengers on the city’s Line 5.
-
A.
Mirabeau station
Mirabeau station is a Paris Métro station in the 16th arrondissement, notable for its single-direction platform layout and proximity to the Pont Mirabeau over the Seine.
-
B.
Malesherbes station
Malesherbes station is a railway station in France serving the town of Malesherbes and connecting it to the regional rail network.
-
C.
Malesherbes station
Malesherbes station is a Paris Métro station serving the 8th and 17th arrondissements of Paris on Line 3.
-
D.
Fabre station
Fabre station is a Montreal Metro station on the Blue Line serving the Rosemont–La Petite-Patrie borough.
-
E.
Beaurepaire station
Beaurepaire station is a commuter rail station serving the Beaurepaire area of Beaconsfield, a suburb on the Island of Montreal in Quebec, Canada.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9158b34648190b5eecdf9b07fbb3f |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e48957081909c4598e82ab31e1f |
completed | May 2, 2026, 3:54 p.m. |
| NEDg | Description generation | batch_69f61f5b107c819082094791fcf7c5f4 |
completed | May 2, 2026, 3:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f62006afcc8190b8e3b55a5fd8eaca |
completed | May 2, 2026, 4:02 p.m. |
Created at: April 8, 2026, 9:49 p.m.