Triple
T15777622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baku Metro |
E382528
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Green Line
The Green Line is one of the main rapid transit lines in the Baku Metro system serving the city of Baku, Azerbaijan.
|
E1181265
|
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: Green Line | Statement: [Baku Metro, hasLine, Green Line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Green Line Context triple: [Baku Metro, hasLine, Green Line]
-
A.
Green Line
The Green Line is one of the main rapid transit routes of the Dubai Metro, serving key districts along Dubai Creek and connecting important commercial and residential areas.
-
B.
Green Line
Green Line is a hybrid-oriented trim level of the Saturn Aura midsize sedan designed to offer improved fuel efficiency and lower emissions.
-
C.
Green Line
The Green Line is one of the main rapid transit corridors of the Chennai Metro system in Chennai, India, connecting key areas of the city via elevated and underground stations.
-
D.
Green Line
The Green Line is one of the light rail routes in Houston’s METRORail system, serving the city’s East End and connecting it to downtown.
-
E.
Green Line
The Green Line is a rapid transit route within Miami-Dade County's Metrorail system, providing north-south rail service through key urban neighborhoods and connections.
- 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: Green Line Triple: [Baku Metro, hasLine, Green Line]
Generated description
The Green Line is one of the main rapid transit lines in the Baku Metro system serving the city of Baku, Azerbaijan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Green Line Target entity description: The Green Line is one of the main rapid transit lines in the Baku Metro system serving the city of Baku, Azerbaijan.
-
A.
Green Line
The Green Line is one of the main rapid transit routes of the Dubai Metro, serving key districts along Dubai Creek and connecting important commercial and residential areas.
-
B.
Green Line
The Green Line is one of the main rapid transit corridors of Bengaluru’s Namma Metro system, running north–south across the city.
-
C.
Green Line
The Green Line is one of the color-coded rapid transit routes in Atlanta’s MARTA rail system, serving key stations on the city’s east–west corridor.
-
D.
Green Line
The Green Line is one of the main lines of the Lisbon Metro rapid transit system, serving several central and riverside neighborhoods of Portugal’s capital.
-
E.
Green Line
The Green Line is one of the color-coded rapid transit routes in the Washington Metro system, serving key neighborhoods in Washington, D.C. and parts of Maryland.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05199cd8881909462462cec34d35a |
completed | April 16, 2026, 3:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa9361f5c8190b68702154d05bbc2 |
completed | May 9, 2026, 9:37 p.m. |
| NEDg | Description generation | batch_69ffaa3903408190b7beaa6b461bd2bd |
completed | May 9, 2026, 9:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffab0c79d4819085f0ed6a4edcb7fb |
completed | May 9, 2026, 9:45 p.m. |
Created at: April 10, 2026, 4:47 a.m.