Triple
T7114675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sofia Metro |
E165788
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line 2
Line 2 is one of the main lines of the Sofia Metro rapid transit system in Sofia, Bulgaria, connecting key residential districts with the city center and major transport hubs.
|
E641772
|
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: Line 2 | Statement: [Sofia Metro, hasLine, Line 2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 2 Context triple: [Sofia Metro, hasLine, Line 2]
-
A.
Line 2
Line 2 is a circular rapid transit line of the Beijing Subway that runs around the city center, roughly following the path of the old city walls and the 2nd Ring Road.
-
B.
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.
-
C.
Line 2
Line 2 is a major route of the Tunis Metro light rail network, serving key districts within the Tunis metropolitan area.
-
D.
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.
-
E.
Line 2
Line 2 is a major rapid transit route of the Santo Domingo Metro system in the Dominican Republic, serving key east–west corridors of the capital.
- 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: Line 2 Triple: [Sofia Metro, hasLine, Line 2]
Generated description
Line 2 is one of the main lines of the Sofia Metro rapid transit system in Sofia, Bulgaria, connecting key residential districts with the city center and major transport hubs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 2 Target entity description: Line 2 is one of the main lines of the Sofia Metro rapid transit system in Sofia, Bulgaria, connecting key residential districts with the city center and major transport hubs.
-
A.
Line 2
Line 2 is one of the main rapid transit routes of the Athens Metro, connecting key central and suburban areas of the Greek capital.
-
B.
Line 2
Line 2 is a major rapid transit route of the STC Metro system, serving key districts along one of the network’s primary corridors.
-
C.
Line 2
Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
-
D.
Line 2
Line 2 is a major route of the Tunis Metro light rail network, serving key districts within the Tunis metropolitan area.
-
E.
Line 2
Line 2 is one of the main lines of the Santiago Metro in Chile, running in a generally north–south direction and serving several central and densely populated areas of the 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5f0dab8819092103aefcaa1f9c2 |
completed | March 27, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79cbfc7a08190ab07f3d65aa79f16 |
completed | March 28, 2026, 9:17 a.m. |
| NEDg | Description generation | batch_69c79d0215888190b0e59c2584358a05 |
completed | March 28, 2026, 9:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c79d63b6dc8190b3b52ef6566ba490 |
completed | March 28, 2026, 9:20 a.m. |
Created at: March 27, 2026, 2:43 p.m.