Triple
T17118641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helsinki public transport network |
E415404
|
entity |
| Predicate | hasMetroLine |
P17559
|
FINISHED |
| Object |
M2
M2 is one of the main metro lines in Helsinki’s public transportation system, serving key districts across the city and its surrounding areas.
|
E1250914
|
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: M2 | Statement: [Helsinki public transport network, hasMetroLine, M2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M2 Context triple: [Helsinki public transport network, hasMetroLine, M2]
-
A.
M2
M2 is a major British motorway that connects London with the port town of Dover in Kent, serving as an important route to the Channel ports.
-
B.
M2
M2 was the original name of MTV2, a U.S. cable television channel that focused on music videos and youth-oriented programming.
-
C.
M2
M2 is one of the main lines of the Budapest Metro, running east–west across the city and connecting several key transport hubs.
-
D.
M2
M2 is a boat line that operates as part of Geneva’s public transport network, providing passenger services across the city’s waters.
-
E.
M2
M2 is a central Manchester, England postcode district covering part of the city’s main commercial and business 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: M2 Triple: [Helsinki public transport network, hasMetroLine, M2]
Generated description
M2 is one of the main metro lines in Helsinki’s public transportation system, serving key districts across the city and its surrounding areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: M2 Target entity description: M2 is one of the main metro lines in Helsinki’s public transportation system, serving key districts across the city and its surrounding areas.
-
A.
M2
M2 is one of the main lines of the Copenhagen Metro, connecting central Copenhagen with key districts and the airport.
-
B.
M2
M2 is one of the main lines of the Budapest Metro, running east–west across the city and connecting several key transport hubs.
-
C.
M2
M2 is one of the main lines of the Bucharest Metro, running on a north–south axis and serving several of the city’s key residential and commercial areas.
-
D.
M2
M2 is the second line of the Warsaw Metro, running east–west across the city and connecting key districts on both sides of the Vistula River.
-
E.
M2
M2 is a metro line in Lausanne, Switzerland, forming part of the city's urban rapid transit 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e8086a388190a655a044feccab14 |
completed | April 18, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a013a0e11108190bfcf858142aa9ff3 |
completed | May 11, 2026, 2:08 a.m. |
| NEDg | Description generation | batch_6a013b749680819097159f0fdc379f2c |
completed | May 11, 2026, 2:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a013bf9ef508190aac1155680f33eaf |
completed | May 11, 2026, 2:16 a.m. |
Created at: April 10, 2026, 5:35 a.m.