Triple
T3528792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lausanne |
E74605
|
entity |
| Predicate | hasMetroLine |
P17559
|
FINISHED |
| Object |
M1
M1 is a light metro line in Lausanne, Switzerland, connecting the city center with the university and lakeside areas.
|
E365742
|
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: M1 | Statement: [Lausanne, hasMetroLine, M1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M1 Context triple: [Lausanne, hasMetroLine, M1]
-
A.
M1
M1 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across the city’s waters.
-
B.
M1
M1 is the first and primary north–south metro line of the Warsaw Metro system in Poland.
-
C.
M1
M1 is one of the main lines of the Copenhagen Metro, providing rapid transit service through central Copenhagen and connecting key residential and commercial areas.
-
D.
M1
M1 is Budapest’s historic Millennium Underground line, one of the world’s oldest metro lines and a UNESCO World Heritage site.
-
E.
M11
M11 is a major motorway in England that connects London to Cambridge and the East Anglia region.
- 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: M1 Triple: [Lausanne, hasMetroLine, M1]
Generated description
M1 is a light metro line in Lausanne, Switzerland, connecting the city center with the university and lakeside areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: M1 Target entity description: M1 is a light metro line in Lausanne, Switzerland, connecting the city center with the university and lakeside areas.
-
A.
M1
M1 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across the city’s waters.
-
B.
M1
M1 is the first and primary north–south metro line of the Warsaw Metro system in Poland.
-
C.
M1
M1 is one of the main lines of the Copenhagen Metro, providing rapid transit service through central Copenhagen and connecting key residential and commercial areas.
-
D.
M1
M1 is Budapest’s historic Millennium Underground line, one of the world’s oldest metro lines and a UNESCO World Heritage site.
-
E.
M11
M11 is a major motorway in England that connects London to Cambridge and the East Anglia region.
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc6e9188819093480b39f263ce75 |
completed | March 8, 2026, 6:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e93c1988190a9ab7698bf63e8e6 |
completed | March 13, 2026, 3:03 a.m. |
| NEDg | Description generation | batch_69b380a6b6ec8190be0741cb9535b650 |
completed | March 13, 2026, 3:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b3812927e48190a84f3c7fa55d070a |
completed | March 13, 2026, 3:14 a.m. |
Created at: March 8, 2026, 3:19 p.m.