Triple
T14036965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 2 (Athens Metro) |
E337736
|
entity |
| Predicate | hasLocalName |
P6353
|
FINISHED |
| Object |
Γραμμή 2
Γραμμή 2 is one of the main lines of the Athens Metro system, connecting key central and southern districts of Athens.
|
E1075055
|
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: Γραμμή 2 | Statement: [Line 2 (Athens Metro), hasLocalName, Γραμμή 2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Γραμμή 2 Context triple: [Line 2 (Athens Metro), hasLocalName, Γραμμή 2]
-
A.
Line 2
Line 2 is a major east–west rapid transit route of the Shanghai Metro that connects key commercial, residential, and airport hubs across the city.
-
B.
Line 2
Line 2 is a major rapid transit route of the Guangzhou Metro system that runs through key urban districts and serves as one of the network’s primary north–south corridors.
-
C.
Line 2
Line 2 is a circular line of the Brussels Metro system that serves central and surrounding districts of the Belgian capital.
-
D.
Line 2
Line 2 is a major east–west rapid transit route in the Shenzhen Metro system, connecting key commercial and residential districts across the city.
-
E.
Line 2
Line 2 is a proposed future line of the Seville Metro intended to expand the city's rapid transit network.
- 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: Γραμμή 2 Triple: [Line 2 (Athens Metro), hasLocalName, Γραμμή 2]
Generated description
Γραμμή 2 is one of the main lines of the Athens Metro system, connecting key central and southern districts of Athens.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Γραμμή 2 Target entity description: Γραμμή 2 is one of the main lines of the Athens Metro system, connecting key central and southern districts of Athens.
-
A.
Line 2
Line 2 is a trolleybus route within Geneva’s public transport system that serves as one of the city’s main electric bus lines.
-
B.
Line 2
Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
-
C.
Line 2
Line 2 is a major circular line of the Seoul Metropolitan Subway system, known for being one of the busiest and most important routes in the network.
-
D.
Line 2
Line 2 is one of the commuter rail lines of the Biotrén system serving the Greater Concepción area in Chile.
-
E.
Line 2
Line 2 is a circular line of the Brussels Metro system that serves central and surrounding districts of the Belgian capital.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de30e312148190a6be0a3258364e6e |
completed | April 14, 2026, 12:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc33bc20081909abea7e64d1bd578 |
completed | May 6, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69fbc53729d081908b74532d2ed54b7a |
completed | May 6, 2026, 10:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fbc5d76cdc8190970778580437cf72 |
completed | May 6, 2026, 10:51 p.m. |
Created at: April 9, 2026, 10:20 p.m.