Triple
T15506302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyon Metro line A |
E379090
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Foch station
Foch station is an underground metro stop on the Lyon Metro network in Lyon, France, serving passengers on line A.
|
E1170532
|
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: Foch station | Statement: [Lyon Metro line A, hasStation, Foch station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Foch station Context triple: [Lyon Metro line A, hasStation, Foch station]
-
A.
Vaucelles station
Vaucelles station is a railway station serving the commune of Taverny in the northern suburbs of Paris, France.
-
B.
Bréguet-Sabin station
Bréguet-Sabin station is a Paris Métro station on Line 5 located in the 11th arrondissement of Paris, France.
-
C.
Malesherbes station
Malesherbes station is a Paris Métro station serving the 8th and 17th arrondissements of Paris on Line 3.
-
D.
Malesherbes station
Malesherbes station is a railway station in France serving the town of Malesherbes and connecting it to the regional rail network.
-
E.
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.
- 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: Foch station Triple: [Lyon Metro line A, hasStation, Foch station]
Generated description
Foch station is an underground metro stop on the Lyon Metro network in Lyon, France, serving passengers on line A.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Foch station Target entity description: Foch station is an underground metro stop on the Lyon Metro network in Lyon, France, serving passengers on line A.
-
A.
Vaucelles station
Vaucelles station is a railway station serving the commune of Taverny in the northern suburbs of Paris, France.
-
B.
Bréguet-Sabin station
Bréguet-Sabin station is a Paris Métro station on Line 5 located in the 11th arrondissement of Paris, France.
-
C.
Malesherbes station
Malesherbes station is a Paris Métro station serving the 8th and 17th arrondissements of Paris on Line 3.
-
D.
Malesherbes station
Malesherbes station is a railway station in France serving the town of Malesherbes and connecting it to the regional rail network.
-
E.
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.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcea8888190a7b69aca360183c3 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ec6b5ac8190abeb944857d912e6 |
completed | May 9, 2026, 5:28 p.m. |
| NEDg | Description generation | batch_69ff6fc55c2c8190a94517888143ee61 |
completed | May 9, 2026, 5:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff703fe0088190ab5578d3d398ca09 |
completed | May 9, 2026, 5:34 p.m. |
Created at: April 10, 2026, 3:55 a.m.