Triple
T14122782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bella Center |
E339943
|
entity |
| Predicate | metroLine |
P848
|
FINISHED |
| Object |
M1 line
The M1 line is one of the main lines of the Copenhagen Metro, connecting central Copenhagen with districts such as Ørestad and Vestamager.
|
E1081259
|
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 line | Statement: [Bella Center, metroLine, M1 line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M1 line Context triple: [Bella Center, metroLine, M1 line]
-
A.
M1 line
The M1 line is a primary rapid transit route of the Ankara Metro system serving key districts of Turkey’s capital city.
-
B.
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.
-
C.
M1 line
The M1 line is a light metro route in Lausanne, Switzerland, connecting the city center with the university and lakeside areas as part of the Lausanne Métro network.
-
D.
M1 line
The M1 line is one of the main rapid transit routes of the Istanbul Metro, connecting central districts with key transport hubs such as the airport and intercity bus terminal.
-
E.
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.
- 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 line Triple: [Bella Center, metroLine, M1 line]
Generated description
The M1 line is one of the main lines of the Copenhagen Metro, connecting central Copenhagen with districts such as Ørestad and Vestamager.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: M1 line Target entity description: The M1 line is one of the main lines of the Copenhagen Metro, connecting central Copenhagen with districts such as Ørestad and Vestamager.
-
A.
M1 line
The M1 line is a primary rapid transit route of the Ankara Metro system serving key districts of Turkey’s capital city.
-
B.
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.
-
C.
M1 line
The M1 line is a light metro route in Lausanne, Switzerland, connecting the city center with the university and lakeside areas as part of the Lausanne Métro network.
-
D.
M1 line
The M1 line is one of the main rapid transit routes of the Istanbul Metro, connecting central districts with key transport hubs such as the airport and intercity bus terminal.
-
E.
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.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6095548881908a9e66adccca92d2 |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf07feb48190b7519204b4f789b4 |
completed | May 7, 2026, 6:50 p.m. |
| NEDg | Description generation | batch_69fce0f2dcc48190952ea89af5c809d7 |
completed | May 7, 2026, 6:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fce1792ae48190a9379abff92f0f9e |
completed | May 7, 2026, 7:01 p.m. |
Created at: April 9, 2026, 10:22 p.m.