Triple
T17118640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helsinki public transport network |
E415404
|
entity |
| Predicate | hasMetroLine |
P17559
|
FINISHED |
| Object |
M1
M1 is one of the main metro lines in the Helsinki public transport system, serving key districts across the Helsinki metropolitan area.
|
E1250913
|
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: [Helsinki public transport network, hasMetroLine, M1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M1 Context triple: [Helsinki public transport network, hasMetroLine, M1]
-
A.
M1
M1 is the first and primary north–south metro line of the Warsaw Metro system in Poland.
-
B.
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.
-
C.
M1
M1 is a major north–south urban freeway in Johannesburg, South Africa, connecting the city center with key suburbs and routes.
-
D.
M1
M1 is the main primary mirror of the Extremely Large Telescope, responsible for collecting and focusing incoming light for its observations.
-
E.
M1
M1 is a major Irish motorway that connects Dublin to the border with Northern Ireland, forming part of the primary route between the Republic of Ireland and Belfast.
- 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: [Helsinki public transport network, hasMetroLine, M1]
Generated description
M1 is one of the main metro lines in the Helsinki public transport system, serving key districts across the Helsinki metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: M1 Target entity description: M1 is one of the main metro lines in the Helsinki public transport system, serving key districts across the Helsinki metropolitan area.
-
A.
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.
-
B.
M1
M1 is one of the main lines of the Bucharest Metro, forming part of the city’s core rapid transit network.
-
C.
M1
M1 is the first and primary north–south metro line of the Warsaw Metro system in Poland.
-
D.
M1
M1 is a light metro line in Lausanne, Switzerland, connecting the city center with the university and lakeside areas.
-
E.
M1
M1 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across the city’s waters.
- 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.