Triple
T21355944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boulevard de Grenelle |
E526623
|
entity |
| Predicate | hasMetroStation |
P522
|
FINISHED |
| Object |
Dupleix station
Dupleix station is a Paris Métro station in the 15th arrondissement, serving Line 6 near the Eiffel Tower.
|
E1489824
|
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: Dupleix station | Statement: [Boulevard de Grenelle, hasMetroStation, Dupleix station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dupleix station Context triple: [Boulevard de Grenelle, hasMetroStation, Dupleix station]
-
A.
Caussade station
Caussade station is a regional railway station in the town of Caussade in southern France, serving local and regional train services.
-
B.
Raspail station
Raspail station is a Paris Métro station serving lines 4 and 6, located in the city's 14th arrondissement.
-
C.
Falguière station
Falguière station is a Paris Métro station in the Montparnasse area, serving Line 12 in the 15th arrondissement of Paris.
-
D.
Saint-Just station
Saint-Just station is a terminal stop on Lyon’s historic funicular network, serving the Saint-Just neighborhood in the city’s Fourvière area.
-
E.
Malesherbes station
Malesherbes station is a railway station in France serving the town of Malesherbes and connecting it to the regional rail network.
- 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: Dupleix station Triple: [Boulevard de Grenelle, hasMetroStation, Dupleix station]
Generated description
Dupleix station is a Paris Métro station in the 15th arrondissement, serving Line 6 near the Eiffel Tower.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dupleix station Target entity description: Dupleix station is a Paris Métro station in the 15th arrondissement, serving Line 6 near the Eiffel Tower.
-
A.
Caussade station
Caussade station is a regional railway station in the town of Caussade in southern France, serving local and regional train services.
-
B.
Raspail station
Raspail station is a Paris Métro station serving lines 4 and 6, located in the city's 14th arrondissement.
-
C.
Falguière station
Falguière station is a Paris Métro station in the Montparnasse area, serving Line 12 in the 15th arrondissement of Paris.
-
D.
Saint-Just station
Saint-Just station is a terminal stop on Lyon’s historic funicular network, serving the Saint-Just neighborhood in the city’s Fourvière area.
-
E.
Malesherbes station
Malesherbes station is a railway station in France serving the town of Malesherbes and connecting it to the regional rail network.
- 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_69e0b51d8a308190b09113b3b3f9bc15 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8af9cd4a48190aa6e72c019b60f8c |
completed | April 22, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09eec9df648190838800dcfe6378de |
completed | May 17, 2026, 4:37 p.m. |
| NEDg | Description generation | batch_6a09ef8209c48190a5c591f0cc7e601f |
completed | May 17, 2026, 4:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09eff8ee408190a0ed72fe19bfcee2 |
completed | May 17, 2026, 4:42 p.m. |
Created at: April 16, 2026, 5:06 p.m.