Triple
T15299384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M2 (Lausanne Metro) |
E365743
|
entity |
| Predicate | servesStation |
P839
|
FINISHED |
| Object |
Bessières
Bessières is a metro station on the Lausanne Métro network in Lausanne, Switzerland.
|
E1212085
|
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: Bessières | Statement: [M2 (Lausanne Metro), servesStation, Bessières]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bessières Context triple: [M2 (Lausanne Metro), servesStation, Bessières]
-
A.
Beaujeu
Beaujeu is the pseudonym of Jean Monceau, under which he is known in his professional and public activities.
-
B.
Saussignac
Saussignac is a small wine-producing commune in southwestern France, known for its sweet white wines made primarily from Sémillon and other Bordeaux grape varieties.
-
C.
Roquebillière
Roquebillière is a small commune in southeastern France, situated in the Alpes-Maritimes department in the Provence-Alpes-Côte d’Azur region.
-
D.
Bévilard
Bévilard is a village in the Bernese Jura region of the canton of Bern in Switzerland.
-
E.
Mouriès
Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
- 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: Bessières Triple: [M2 (Lausanne Metro), servesStation, Bessières]
Generated description
Bessières is a metro station on the Lausanne Métro network in Lausanne, Switzerland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bessières Target entity description: Bessières is a metro station on the Lausanne Métro network in Lausanne, Switzerland.
-
A.
Beaujeu
Beaujeu is the pseudonym of Jean Monceau, under which he is known in his professional and public activities.
-
B.
Saussignac
Saussignac is a small wine-producing commune in southwestern France, known for its sweet white wines made primarily from Sémillon and other Bordeaux grape varieties.
-
C.
Roquebillière
Roquebillière is a small commune in southeastern France, situated in the Alpes-Maritimes department in the Provence-Alpes-Côte d’Azur region.
-
D.
Bévilard
Bévilard is a village in the Bernese Jura region of the canton of Bern in Switzerland.
-
E.
Mouriès
Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03686bfb8819080ba0caae652170a |
completed | April 16, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c4303888190a93830ef534715ae |
completed | May 10, 2026, 8:05 a.m. |
| NEDg | Description generation | batch_6a003ec3c3c481909f2ad743b3cb486e |
completed | May 10, 2026, 8:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a003f300e688190a12352fef2f801f9 |
completed | May 10, 2026, 8:17 a.m. |
Created at: April 10, 2026, 3:15 a.m.