Triple
T4098510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helsinki Metro |
E87880
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
M2 line
The M2 line is one of the main lines of the Helsinki Metro rapid transit system, serving key districts across the Helsinki metropolitan area.
|
E415401
|
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 line | Statement: [Helsinki Metro, hasLine, M2 line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M2 line Context triple: [Helsinki Metro, hasLine, M2 line]
-
A.
M2 line
The M2 line is a major rapid transit route within the Ankara Metro system in Turkey, serving key districts of the capital city.
-
B.
M3 line
The M3 line is a rapid transit route within the Ankara Metro system serving parts of Turkey’s capital city.
-
C.
M1 line
The M1 line is a primary rapid transit route of the Ankara Metro system serving key districts of Turkey’s capital city.
-
D.
M1 line
The M1 line is one of the main lines of the Helsinki Metro, running east–west through the Helsinki region and serving several key suburban and central stations.
-
E.
M4 line
The M4 line is a rapid transit route within the Ankara Metro system serving passengers in Turkey’s capital city.
- 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 line Triple: [Helsinki Metro, hasLine, M2 line]
Generated description
The M2 line is one of the main lines of the Helsinki Metro rapid transit system, serving key districts across the Helsinki metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: M2 line Target entity description: The M2 line is one of the main lines of the Helsinki Metro rapid transit system, serving key districts across the Helsinki metropolitan area.
-
A.
M2 line
The M2 line is a major rapid transit route within the Ankara Metro system in Turkey, serving key districts of the capital city.
-
B.
M3 line
The M3 line is a rapid transit route within the Ankara Metro system serving parts of Turkey’s capital city.
-
C.
M1 line
The M1 line is a primary rapid transit route of the Ankara Metro system serving key districts of Turkey’s capital city.
-
D.
M1 line
The M1 line is one of the main lines of the Helsinki Metro, running east–west through the Helsinki region and serving several key suburban and central stations.
-
E.
M4 line
The M4 line is a rapid transit route within the Ankara Metro system serving passengers in Turkey’s capital city.
- 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_69aed94564cc8190a9c1457daedb6e7f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd0bdea48190805a79515ee92709 |
completed | March 9, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b576a1a0408190aa4683a0904790aa |
completed | March 14, 2026, 2:54 p.m. |
| NEDg | Description generation | batch_69b576fb7fa08190ada0dff7aa581665 |
completed | March 14, 2026, 2:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5778dcdc08190aee087f6d54992dc |
completed | March 14, 2026, 2:58 p.m. |
Created at: March 9, 2026, 3:40 p.m.